---------------------------------------------------------------------------------------------------------------
      name:  <unnamed>
       log:  /Users/006489466/Dropbox/Depolicing/SubmissionFiles/FergEff/PolicingOX/RnR Round 2/New Analysis Pt
>  2/FergEffTestsStops.log
  log type:  text
 opened on:   4 May 2022, 15:57:40

. 
. *Vehicle Stops
. xtset PanelID MonthYear, monthly
       panel variable:  PanelID (unbalanced)
        time variable:  MonthYear, 2011m1 to 2016m12, but with gaps
                delta:  1 month

. xtnbreg Vehicle FergEff1 d.UnempL d.OffRateL d.DepScore d.PctNonWhtL  ///
> i.MonthYear if NoCov < 1, fe irr vce(bootstrap, seed(909) ///
> reps(5000) nodots) exposure(population)
note: 655.MonthYear omitted because of collinearity
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered

Conditional FE negative binomial regression     Number of obs     =      2,628
Group variable: PanelID                         Number of groups  =         44

                                                Obs per group:
                                                              min =         34
                                                              avg =       59.7
                                                              max =         71

                                                Wald chi2(74)     =   21040.39
Log likelihood  = -21157.609                    Prob > chi2       =     0.0000

                                (Replications based on 44 clusters in PanelID)
------------------------------------------------------------------------------
             |   Observed   Bootstrap                         Normal-based
     Vehicle |        IRR   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    FergEff1 |   .8421575   .0527741    -2.74   0.006     .7448219    .9522132
             |
      UnempL |
         D1. |   .8078829    .136987    -1.26   0.208     .5794503    1.126369
             |
    OffRateL |
         D1. |   .8658941     .41465    -0.30   0.764     .3387276    2.213497
             |
    DepScore |
         D1. |   .8658271   .0919117    -1.36   0.175     .7031889    1.066081
             |
  PctNonWhtL |
         D1. |   3.960635   8.249885     0.66   0.509      .066794    234.8509
             |
   MonthYear |
        614  |    1.13772   .0391619     3.75   0.000     1.063496    1.217125
        615  |   1.008187   .0308921     0.27   0.790     .9494216    1.070589
        616  |   1.052747    .043084     1.26   0.209     .9716018    1.140669
        617  |    1.03748   .0384055     0.99   0.320     .9648728    1.115552
        618  |   1.010122   .0395265     0.26   0.797     .9355476    1.090641
        619  |   1.007454   .0527118     0.14   0.887      .909262    1.116251
        620  |   .9403123   .0465703    -1.24   0.214     .8533264    1.036165
        621  |   .8796487   .0386291    -2.92   0.003     .8071038    .9587142
        622  |   .8685278   .0373008    -3.28   0.001      .798412    .9448011
        623  |   .8450768   .0487977    -2.92   0.004     .7546487    .9463407
        624  |   .9888625   .0607851    -0.18   0.855     .8766228    1.115473
        625  |   .9594729   .0546359    -0.73   0.468      .858148    1.072762
        626  |   .9646506    .065718    -0.53   0.597     .8440748    1.102451
        627  |   .8664902    .053199    -2.33   0.020     .7682514    .9772911
        628  |   .9365163   .0590391    -1.04   0.298     .8276651    1.059683
        629  |   .8878245   .0530996    -1.99   0.047     .7896196    .9982432
        630  |   .8806283   .0497688    -2.25   0.024     .7882916    .9837808
        631  |   .9053779   .0559862    -1.61   0.108      .802036    1.022035
        632  |   .8120518   .0493247    -3.43   0.001       .72091    .9147164
        633  |   .8483217   .0497956    -2.80   0.005      .756129    .9517552
        634  |    .832359   .0540585    -2.83   0.005     .7328725    .9453507
        635  |   .7612889   .0538413    -3.86   0.000     .6627493    .8744796
        636  |   .9251685   .0630603    -1.14   0.254     .8094726      1.0574
        637  |   .8247738    .057352    -2.77   0.006     .7196895    .9452017
        638  |   .9583707   .0654353    -0.62   0.533     .8383309    1.095599
        639  |   .8406354   .0572147    -2.55   0.011     .7356544    .9605977
        640  |   .8914091   .0598479    -1.71   0.087     .7814994    1.016776
        641  |   .8001216   .0519425    -3.43   0.001     .7045267    .9086875
        642  |   .8080689   .0526376    -3.27   0.001     .7112154    .9181119
        643  |   .8679694   .0594913    -2.07   0.039     .7588613    .9927649
        644  |   .8069883   .0600945    -2.88   0.004     .6973972    .9338008
        645  |   .8642727   .0693352    -1.82   0.069     .7385233    1.011434
        646  |   .8376444   .0650106    -2.28   0.022     .7194437    .9752647
        647  |   .7730028   .0620322    -3.21   0.001      .660501    .9046667
        648  |   .9110074    .072962    -1.16   0.245     .7786633    1.065845
        649  |   .8690821   .0611733    -1.99   0.046     .7570875    .9976438
        650  |   .9142487   .0613452    -1.34   0.182     .8015849    1.042748
        651  |   .8744259   .0638999    -1.84   0.066       .75774     1.00908
        652  |   .9042175    .064168    -1.42   0.156     .7868051    1.039151
        653  |    .812122   .0540279    -3.13   0.002     .7128425    .9252285
        654  |   .8596311   .0543631    -2.39   0.017     .7594201    .9730656
        655  |          1  (omitted)
        656  |   .7931394   .0490484    -3.75   0.000     .7026038    .8953411
        657  |   .7969328   .0516891    -3.50   0.000      .701799    .9049628
        658  |   .7283887   .0515069    -4.48   0.000     .6341205    .8366709
        659  |   .6628201   .0478269    -5.70   0.000     .5754078    .7635114
        660  |   .7812381   .0686006    -2.81   0.005     .6577174    .9279563
        661  |   .7396006   .0568141    -3.93   0.000     .6362243    .8597738
        662  |   .7963068   .0657749    -2.76   0.006     .6772846    .9362452
        663  |    .769938   .0624429    -3.22   0.001     .6567836    .9025872
        664  |   .7704659   .0564541    -3.56   0.000     .6673961    .8894534
        665  |   .7384505   .0576788    -3.88   0.000     .6336301    .8606111
        666  |   .7580065   .0656179    -3.20   0.001     .6397164    .8981697
        667  |   .7638131   .0613487    -3.35   0.001     .6525586    .8940354
        668  |   .7281986   .0549931    -4.20   0.000     .6280116    .8443686
        669  |   .7500524   .0593773    -3.63   0.000     .6422542     .875944
        670  |   .7095164   .0564043    -4.32   0.000      .607148    .8291446
        671  |   .6753524   .0549348    -4.83   0.000     .5758266    .7920803
        672  |   .7706851   .0744645    -2.70   0.007     .6377242    .9313674
        673  |    .786412   .0741196    -2.55   0.011     .6537687    .9459674
        674  |   .8086346   .0751833    -2.28   0.022     .6739246    .9702717
        675  |   .7176395     .06677    -3.57   0.000     .5980116    .8611981
        676  |   .7693785   .0710911    -2.84   0.005     .6419312    .9221289
        677  |   .7556845   .0903332    -2.34   0.019      .597846    .9551943
        678  |   .6849327   .0739566    -3.50   0.000     .5542915    .8463648
        679  |   .7717479   .0736375    -2.72   0.007     .6401132    .9304523
        680  |   .7330456   .0715699    -3.18   0.001     .6053759      .88764
        681  |    .699738   .0781875    -3.20   0.001     .5621131    .8710584
        682  |   .6517807   .0744053    -3.75   0.000     .5211118    .8152148
        683  |   .6406032   .0768291    -3.71   0.000     .5064102     .810356
             |
       _cons |   .0000407   8.18e-06   -50.35   0.000     .0000275    .0000604
ln(popula~n) |          1  (exposure)
------------------------------------------------------------------------------
Note: _cons estimates baseline incidence rate (conditional on zero random effects).
Note: One or more parameters could not be estimated in 96 bootstrap replicates;
      standard-error estimates include only complete replications.

. estat ic

Akaike's information criterion and Bayesian information criterion

-----------------------------------------------------------------------------
       Model |        Obs  ll(null)  ll(model)      df         AIC        BIC
-------------+---------------------------------------------------------------
           . |      2,628         .  -21157.61      75    42465.22   42905.77
-----------------------------------------------------------------------------
               Note: N=Obs used in calculating BIC; see [R] BIC note.

. 
. xtset PanelID MonthYear, monthly
       panel variable:  PanelID (unbalanced)
        time variable:  MonthYear, 2011m1 to 2016m12, but with gaps
                delta:  1 month

. xtnbreg Vehicle FergEff6 d.UnempL d.OffRateL d.DepScore d.PctNonWhtL  ///
> i.MonthYear if NoCov < 1, fe irr vce(bootstrap, seed(909) ///
> reps(5000) nodots) exposure(population)
note: 661.MonthYear omitted because of collinearity
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered

Conditional FE negative binomial regression     Number of obs     =      2,628
Group variable: PanelID                         Number of groups  =         44

                                                Obs per group:
                                                              min =         34
                                                              avg =       59.7
                                                              max =         71

                                                Wald chi2(74)     =   21108.18
Log likelihood  = -21157.609                    Prob > chi2       =     0.0000

                                (Replications based on 44 clusters in PanelID)
------------------------------------------------------------------------------
             |   Observed   Bootstrap                         Normal-based
     Vehicle |        IRR   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    FergEff6 |   .7396004   .0566966    -3.93   0.000     .6364222    .8595059
             |
      UnempL |
         D1. |   .8078829   .1368158    -1.26   0.208     .5796911    1.125901
             |
    OffRateL |
         D1. |   .8658945    .414177    -0.30   0.763     .3390908    2.211129
             |
    DepScore |
         D1. |   .8658271   .0918791    -1.36   0.175     .7032409    1.066002
             |
  PctNonWhtL |
         D1. |   3.960642   8.235925     0.66   0.508     .0672576    233.2329
             |
   MonthYear |
        614  |    1.13772   .0391582     3.75   0.000     1.063503    1.217116
        615  |   1.008186   .0309014     0.27   0.790     .9494042    1.070608
        616  |   1.052747   .0430551     1.26   0.209     .9716538    1.140608
        617  |    1.03748   .0384477     0.99   0.321     .9647957     1.11564
        618  |   1.010122   .0395425     0.26   0.797     .9355182    1.090674
        619  |   1.007454   .0527342     0.14   0.887      .909222    1.116299
        620  |    .940312   .0466433    -1.24   0.215     .8531962    1.036323
        621  |   .8796484   .0386741    -2.92   0.004     .8070225      .95881
        622  |   .8685275   .0373149    -3.28   0.001     .7983863    .9448309
        623  |   .8450765   .0487755    -2.92   0.004     .7546872    .9462917
        624  |   .9888621   .0607217    -0.18   0.855     .8767327    1.115332
        625  |   .9594726   .0545629    -0.73   0.467     .8582757    1.072601
        626  |   .9646503   .0656505    -0.53   0.597     .8441902    1.102299
        627  |   .8664899   .0531293    -2.34   0.019     .7683722    .9771368
        628  |    .936516   .0588784    -1.04   0.297      .827943    1.059327
        629  |   .8878242   .0529239    -2.00   0.046     .7899257    .9978557
        630  |    .880628   .0496375    -2.26   0.024     .7885217     .983493
        631  |   .9053776   .0558223    -1.61   0.107     .8023203    1.021672
        632  |   .8120515   .0491786    -3.44   0.001      .721164    .9143935
        633  |   .8483214   .0496268    -2.81   0.005     .7564237    .9513837
        634  |   .8323587   .0538972    -2.83   0.005     .7331507    .9449913
        635  |   .7612886   .0536838    -3.87   0.000     .6630176    .8741251
        636  |   .9251682   .0628618    -1.14   0.252     .8098129    1.056955
        637  |   .8247735   .0572267    -2.78   0.005     .7199035    .9449201
        638  |   .9583704   .0652592    -0.62   0.532     .8386326    1.095204
        639  |   .8406351   .0570916    -2.56   0.011     .7358654    .9603216
        640  |   .8914088   .0596682    -1.72   0.086     .7818079    1.016375
        641  |   .8001213    .051791    -3.45   0.001      .704788    .9083499
        642  |   .8080686   .0525435    -3.28   0.001     .7113775    .9179021
        643  |   .8679691   .0593449    -2.07   0.038     .7591119    .9924365
        644  |    .806988   .0599755    -2.89   0.004     .6975986    .9335306
        645  |   .8642725   .0691729    -1.82   0.068      .738795    1.011061
        646  |   .8376441   .0648785    -2.29   0.022      .719666    .9749629
        647  |   .7730025   .0619211    -3.21   0.001      .660687    .9044115
        648  |   .9110072   .0728188    -1.17   0.244      .778903    1.065517
        649  |   .8690818   .0610424    -2.00   0.046     .7573108    .9973489
        650  |   .9142484   .0611982    -1.34   0.180     .8018374    1.042419
        651  |   .8744256   .0637785    -1.84   0.066     .7579461    1.008805
        652  |   .9042172   .0639215    -1.42   0.154     .7872253    1.038596
        653  |   .8121217   .0538731    -3.14   0.002     .7131085    .9248827
        654  |   .8596308   .0542146    -2.40   0.016     .7596769     .972736
        655  |   1.138665   .0478112     3.09   0.002     1.048709    1.236338
        656  |   1.072389   .0487721     1.54   0.124     .9809339     1.17237
        657  |   1.077518    .041139     1.96   0.051     .9998298    1.161242
        658  |   .9848407   .0298719    -0.50   0.615     .9279991    1.045164
        659  |   .8961865   .0381349    -2.58   0.010     .8244754    .9741348
        660  |   1.056297   .0446411     1.30   0.195      .972328    1.147518
        661  |          1  (omitted)
        662  |   .7963065   .0656631    -2.76   0.006     .6774708    .9359873
        663  |   .7699377   .0623312    -3.23   0.001     .6569701    .9023303
        664  |   .7704657   .0563256    -3.57   0.000     .6676139    .8891626
        665  |   .7384502   .0575364    -3.89   0.000     .6338694    .8602857
        666  |   .7580063   .0655199    -3.21   0.001     .6398783    .8979418
        667  |   .7638128   .0612155    -3.36   0.001     .6527814    .8937296
        668  |   .7281984   .0548804    -4.21   0.000     .6282018    .8441123
        669  |   .7500522   .0592585    -3.64   0.000     .6424534    .8756717
        670  |   .7095162   .0562893    -4.33   0.000     .6073407    .8288811
        671  |   .6753522   .0548497    -4.83   0.000     .5759686    .7918845
        672  |   .7706849   .0743185    -2.70   0.007     .6379609    .9310214
        673  |   .7864118    .073931    -2.56   0.011     .6540758    .9455227
        674  |   .8086344    .075014    -2.29   0.022      .674201    .9698733
        675  |   .7176393   .0666858    -3.57   0.000     .5981488        .861
        676  |   .7693783   .0709338    -2.84   0.004     .6421882    .9217593
        677  |   .7556842    .090167    -2.35   0.019     .5981036    .9547822
        678  |   .6849325   .0738306    -3.51   0.000      .554491    .8460596
        679  |   .7717476   .0734444    -2.72   0.006     .6404269    .9299958
        680  |   .7330454   .0714158    -3.19   0.001     .6056252    .8872741
        681  |   .6997378   .0780787    -3.20   0.001     .5622842    .8707927
        682  |   .6517804   .0743196    -3.75   0.000     .5212459    .8150045
        683  |    .640603    .076814    -3.71   0.000     .5064335    .8103181
             |
       _cons |   .0000407   8.17e-06   -50.38   0.000     .0000275    .0000604
ln(popula~n) |          1  (exposure)
------------------------------------------------------------------------------
Note: _cons estimates baseline incidence rate (conditional on zero random effects).
Note: One or more parameters could not be estimated in 95 bootstrap replicates;
      standard-error estimates include only complete replications.

. estat ic

Akaike's information criterion and Bayesian information criterion

-----------------------------------------------------------------------------
       Model |        Obs  ll(null)  ll(model)      df         AIC        BIC
-------------+---------------------------------------------------------------
           . |      2,628         .  -21157.61      75    42465.22   42905.77
-----------------------------------------------------------------------------
               Note: N=Obs used in calculating BIC; see [R] BIC note.

. 
. xtset PanelID MonthYear, monthly
       panel variable:  PanelID (unbalanced)
        time variable:  MonthYear, 2011m1 to 2016m12, but with gaps
                delta:  1 month

. xtnbreg Vehicle FergEff12 d.UnempL d.OffRateL d.DepScore d.PctNonWhtL  ///
> i.MonthYear if NoCov < 1, fe irr vce(bootstrap, seed(909) ///
> reps(5000) nodots) exposure(population)
note: 667.MonthYear omitted because of collinearity
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered

Conditional FE negative binomial regression     Number of obs     =      2,628
Group variable: PanelID                         Number of groups  =         44

                                                Obs per group:
                                                              min =         34
                                                              avg =       59.7
                                                              max =         71

                                                Wald chi2(74)     =   21104.04
Log likelihood  = -21157.609                    Prob > chi2       =     0.0000

                                (Replications based on 44 clusters in PanelID)
------------------------------------------------------------------------------
             |   Observed   Bootstrap                         Normal-based
     Vehicle |        IRR   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   FergEff12 |   .7638131   .0612419    -3.36   0.001     .6527373    .8937906
             |
      UnempL |
         D1. |   .8078829    .136687    -1.26   0.207     .5798722    1.125549
             |
    OffRateL |
         D1. |   .8658941   .4137451    -0.30   0.763     .3394221    2.208968
             |
    DepScore |
         D1. |   .8658271   .0917851    -1.36   0.174     .7033904    1.065776
             |
  PctNonWhtL |
         D1. |   3.960636   8.239093     0.66   0.508     .0671517       233.6
             |
   MonthYear |
        614  |    1.13772    .039191     3.75   0.000     1.063443    1.217185
        615  |   1.008187   .0309277     0.27   0.790      .949356    1.070663
        616  |   1.052747   .0431212     1.25   0.210     .9715346    1.140748
        617  |    1.03748   .0384256     0.99   0.320     .9648363    1.115594
        618  |   1.010122   .0394724     0.26   0.797     .9356457    1.090526
        619  |   1.007454   .0525884     0.14   0.887     .9094802    1.115983
        620  |   .9403123   .0465787    -1.24   0.214     .8533114    1.036184
        621  |   .8796487   .0386361    -2.92   0.004     .8070913     .958729
        622  |   .8685278   .0373162    -3.28   0.001     .7983842     .944834
        623  |   .8450768   .0487261    -2.92   0.004     .7547739    .9461837
        624  |   .9888625   .0607242    -0.18   0.855     .8767287    1.115338
        625  |   .9594729   .0545115    -0.73   0.466      .858366    1.072489
        626  |   .9646506     .06558    -0.53   0.597     .8443115    1.102142
        627  |   .8664902   .0530309    -2.34   0.019     .7685435    .9769196
        628  |   .9365163   .0589074    -1.04   0.297     .8278931    1.059391
        629  |   .8878245   .0529612    -1.99   0.046     .7898608    .9979383
        630  |   .8806282    .049605    -2.26   0.024     .7885791    .9834222
        631  |   .9053779   .0558281    -1.61   0.107     .8023104    1.021686
        632  |   .8120518   .0492078    -3.44   0.001     .7211135    .9144582
        633  |   .8483217    .049624    -2.81   0.005      .756429    .9513777
        634  |    .832359   .0539216    -2.83   0.005     .7331087     .945046
        635  |   .7612889   .0536609    -3.87   0.000     .6630571    .8740736
        636  |   .9251685   .0628372    -1.15   0.252     .8098554    1.056901
        637  |   .8247738   .0572723    -2.77   0.006     .7198257    .9450229
        638  |   .9583707   .0653261    -0.62   0.533     .8385182    1.095354
        639  |   .8406354   .0570662    -2.56   0.011     .7359092    .9602651
        640  |   .8914091   .0597144    -1.72   0.086     .7817289    1.016478
        641  |   .8001216   .0517963    -3.44   0.001     .7047791    .9083621
        642  |   .8080689   .0525308    -3.28   0.001     .7113996    .9178742
        643  |   .8679694   .0593678    -2.07   0.038     .7590729    .9924882
        644  |   .8069883   .0599664    -2.89   0.004     .6976144    .9335101
        645  |   .8642727   .0692086    -1.82   0.069     .7387354    1.011143
        646  |   .8376443   .0648776    -2.29   0.022     .7196677    .9749611
        647  |   .7730028   .0619034    -3.22   0.001     .6607169    .9043712
        648  |   .9110074   .0727004    -1.17   0.243     .7791018    1.065245
        649  |    .869082   .0610135    -2.00   0.046     .7573604    .9972843
        650  |   .9142487   .0611983    -1.34   0.180     .8018374    1.042419
        651  |   .8744259   .0637016    -1.84   0.065     .7580769    1.008632
        652  |   .9042175   .0639945    -1.42   0.155     .7871011     1.03876
        653  |    .812122   .0538927    -3.14   0.002     .7130751    .9249267
        654  |    .859631   .0542347    -2.40   0.017     .7596424    .9727807
        655  |    1.10257   .0523994     2.05   0.040     1.004507    1.210206
        656  |   1.038395    .060281     0.65   0.516     .9267196    1.163527
        657  |   1.043361   .0535466     0.83   0.408     .9435174     1.15377
        658  |   .9536217   .0377789    -1.20   0.231     .8823781    1.030618
        659  |   .8677778   .0356066    -3.46   0.001     .8007226    .9404485
        660  |   1.022813   .0434053     0.53   0.595     .9411823    1.111524
        661  |   .9683005   .0302303    -1.03   0.302     .9108265    1.029401
        662  |   1.042541   .0338091     1.28   0.199     .9783387    1.110957
        663  |   1.008019   .0385217     0.21   0.834     .9352758     1.08642
        664  |    1.00871   .0363886     0.24   0.810     .9398527    1.082612
        665  |   .9667947   .0312897    -1.04   0.297     .9073726    1.030108
        666  |   .9923979   .0290576    -0.26   0.794     .9370493    1.051016
        667  |          1  (omitted)
        668  |   .7281986   .0549096    -4.21   0.000     .6281527    .8441789
        669  |   .7500524   .0593012    -3.64   0.000     .6423819    .8757697
        670  |   .7095164   .0562796    -4.33   0.000     .6073572    .8288591
        671  |   .6753524   .0548264    -4.84   0.000     .5760076    .7918313
        672  |   .7706851   .0742449    -2.70   0.007     .6380805    .9308474
        673  |    .786412    .073944    -2.56   0.011     .6540549    .9455535
        674  |   .8086346   .0750029    -2.29   0.022     .6742194    .9698475
        675  |   .7176395   .0666394    -3.57   0.000     .5982249     .860891
        676  |   .7693785   .0709349    -2.84   0.004     .6421867     .921762
        677  |   .7556845   .0901635    -2.35   0.019     .5981093    .9547738
        678  |   .6849327   .0737648    -3.51   0.000     .5545958    .8459004
        679  |   .7717479   .0734095    -2.72   0.006     .6404838    .9299138
        680  |   .7330456   .0714015    -3.19   0.001     .6056486    .8872404
        681  |    .699738   .0780209    -3.20   0.001     .5623755     .870652
        682  |   .6517807   .0742581    -3.76   0.000     .5213425     .814854
        683  |   .6406032   .0766986    -3.72   0.000     .5066125    .8100324
             |
       _cons |   .0000407   8.16e-06   -50.44   0.000     .0000275    .0000603
ln(popula~n) |          1  (exposure)
------------------------------------------------------------------------------
Note: _cons estimates baseline incidence rate (conditional on zero random effects).
Note: One or more parameters could not be estimated in 72 bootstrap replicates;
      standard-error estimates include only complete replications.

. estat ic

Akaike's information criterion and Bayesian information criterion

-----------------------------------------------------------------------------
       Model |        Obs  ll(null)  ll(model)      df         AIC        BIC
-------------+---------------------------------------------------------------
           . |      2,628         .  -21157.61      75    42465.22   42905.77
-----------------------------------------------------------------------------
               Note: N=Obs used in calculating BIC; see [R] BIC note.

. 
. xtset PanelID MonthYear, monthly
       panel variable:  PanelID (unbalanced)
        time variable:  MonthYear, 2011m1 to 2016m12, but with gaps
                delta:  1 month

. xtnbreg Vehicle FergEff18 d.UnempL d.OffRateL d.DepScore d.PctNonWhtL  ///
> i.MonthYear if NoCov < 1, fe irr vce(bootstrap, seed(909) ///
> reps(5000) nodots) exposure(population)
note: 673.MonthYear omitted because of collinearity
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered

Conditional FE negative binomial regression     Number of obs     =      2,628
Group variable: PanelID                         Number of groups  =         44

                                                Obs per group:
                                                              min =         34
                                                              avg =       59.7
                                                              max =         71

                                                Wald chi2(74)     =   21147.63
Log likelihood  = -21157.609                    Prob > chi2       =     0.0000

                                (Replications based on 44 clusters in PanelID)
------------------------------------------------------------------------------
             |   Observed   Bootstrap                         Normal-based
     Vehicle |        IRR   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   FergEff18 |    .786412   .0740794    -2.55   0.011     .6538342    .9458726
             |
      UnempL |
         D1. |   .8078829   .1365614    -1.26   0.207     .5800488    1.125207
             |
    OffRateL |
         D1. |   .8658943   .4133074    -0.30   0.763     .3397587    2.206781
             |
    DepScore |
         D1. |   .8658271   .0918033    -1.36   0.174     .7033615     1.06582
             |
  PctNonWhtL |
         D1. |   3.960635    8.24343     0.66   0.508     .0670077    234.1019
             |
   MonthYear |
        614  |    1.13772   .0392163     3.74   0.000     1.063397    1.217239
        615  |   1.008187   .0309457     0.27   0.791     .9493227    1.070701
        616  |   1.052747   .0430907     1.26   0.209     .9715897    1.140683
        617  |    1.03748   .0384257     0.99   0.320      .964836    1.115594
        618  |   1.010122   .0395095     0.26   0.797     .9355783    1.090605
        619  |   1.007454   .0526981     0.14   0.887     .9092862    1.116221
        620  |   .9403123    .046657    -1.24   0.215     .8531721    1.036353
        621  |   .8796487   .0386763    -2.92   0.004     .8070189    .9588149
        622  |   .8685278   .0373765    -3.28   0.001     .7982756    .9449625
        623  |   .8450768   .0487306    -2.92   0.004     .7547661    .9461935
        624  |   .9888625   .0607733    -0.18   0.855     .8766434    1.115447
        625  |   .9594729   .0545043    -0.73   0.466     .8583787    1.072473
        626  |   .9646505   .0655381    -0.53   0.596     .8443832    1.102048
        627  |   .8664902   .0529966    -2.34   0.019     .7686032    .9768438
        628  |   .9365163   .0588928    -1.04   0.297     .8279184    1.059359
        629  |   .8878245   .0529913    -1.99   0.046     .7898084    .9980045
        630  |   .8806282   .0496267    -2.26   0.024     .7885408    .9834697
        631  |   .9053779   .0558696    -1.61   0.107     .8022384    1.021777
        632  |   .8120518    .049236    -3.43   0.001     .7210643    .9145205
        633  |   .8483217   .0496963    -2.81   0.005     .7563025    .9515368
        634  |    .832359   .0539791    -2.83   0.005     .7330094    .9451739
        635  |   .7612888   .0536979    -3.87   0.000      .662994    .8741568
        636  |   .9251684   .0629511    -1.14   0.253     .8096599    1.057156
        637  |   .8247737   .0573832    -2.77   0.006     .7196361    .9452718
        638  |   .9583707   .0654081    -0.62   0.533     .8383775    1.095538
        639  |   .8406354   .0571169    -2.55   0.011     .7358221    .9603787
        640  |   .8914091   .0598138    -1.71   0.087     .7815579      1.0167
        641  |   .8001216   .0518666    -3.44   0.001     .7046577    .9085185
        642  |   .8080689   .0525619    -3.28   0.001      .711346    .9179433
        643  |   .8679694    .059428    -2.07   0.039     .7589698     .992623
        644  |   .8069882   .0600232    -2.88   0.004      .697518    .9336391
        645  |   .8642727   .0693058    -1.82   0.069     .7385726    1.011366
        646  |   .8376443   .0649789    -2.28   0.022     .7194971    .9751923
        647  |   .7730027   .0619961    -3.21   0.001     .6605616    .9045837
        648  |   .9110074   .0728888    -1.16   0.244      .778786    1.065677
        649  |    .869082   .0610883    -2.00   0.046     .7572326    .9974525
        650  |   .9142487   .0612955    -1.34   0.181     .8016703    1.042636
        651  |   .8744259   .0637666    -1.84   0.066     .7579666    1.008779
        652  |   .9042174    .064118    -1.42   0.156     .7868903    1.039038
        653  |    .812122   .0539922    -3.13   0.002     .7129039    .9251487
        654  |    .859631   .0543362    -2.39   0.017     .7594667    .9730058
        655  |   1.070886   .0811773     0.90   0.366     .9230364    1.242417
        656  |   1.008554   .0805048     0.11   0.915     .8624914    1.179353
        657  |   1.013378   .0756614     0.18   0.859     .8754244    1.173071
        658  |   .9262177   .0578759    -1.23   0.220     .8194541    1.046891
        659  |   .8428407   .0543965    -2.65   0.008     .7426932    .9564925
        660  |   .9934209   .0645886    -0.10   0.919     .8745633    1.128432
        661  |   .9404747     .05824    -0.99   0.322     .8329817    1.061839
        662  |   1.012582   .0575404     0.22   0.826     .9058585    1.131879
        663  |   .9790516   .0630497    -0.33   0.742     .8629571    1.110764
        664  |    .979723   .0601554    -0.33   0.739     .8686386    1.105013
        665  |   .9390122   .0509197    -1.16   0.246      .844332    1.044309
        666  |   .9638796   .0567808    -0.62   0.532     .8587755    1.081847
        667  |   .9712632   .0581345    -0.49   0.626     .8637512    1.092157
        668  |   .9259759   .0543242    -1.31   0.190     .8253959    1.038812
        669  |   .9537652   .0470038    -0.96   0.337     .8659489    1.050487
        670  |   .9022197   .0441627    -2.10   0.036     .8196847    .9930652
        671  |   .8587768   .0496427    -2.63   0.008     .7667884    .9618008
        672  |   .9800017   .0442104    -0.45   0.654     .8970712    1.070599
        673  |          1  (omitted)
        674  |   .8086346   .0751338    -2.29   0.022     .6740055    .9701552
        675  |   .7176395    .066716    -3.57   0.000     .5980997    .8610712
        676  |   .7693785   .0709985    -2.84   0.004     .6420825    .9219115
        677  |   .7556845   .0902195    -2.35   0.019     .5980223    .9549125
        678  |   .6849327   .0738865    -3.51   0.000     .5544026    .8461951
        679  |   .7717478    .073512    -2.72   0.007     .6403172    .9301557
        680  |   .7330456   .0714719    -3.19   0.001     .6055346    .8874074
        681  |    .699738   .0781078    -3.20   0.001     .5622386    .8708638
        682  |   .6517806   .0743393    -3.75   0.000     .5212152    .8150529
        683  |   .6406032    .076754    -3.72   0.000     .5065266    .8101696
             |
       _cons |   .0000407   8.17e-06   -50.41   0.000     .0000275    .0000603
ln(popula~n) |          1  (exposure)
------------------------------------------------------------------------------
Note: _cons estimates baseline incidence rate (conditional on zero random effects).
Note: One or more parameters could not be estimated in 57 bootstrap replicates;
      standard-error estimates include only complete replications.

. estat ic

Akaike's information criterion and Bayesian information criterion

-----------------------------------------------------------------------------
       Model |        Obs  ll(null)  ll(model)      df         AIC        BIC
-------------+---------------------------------------------------------------
           . |      2,628         .  -21157.61      75    42465.22   42905.77
-----------------------------------------------------------------------------
               Note: N=Obs used in calculating BIC; see [R] BIC note.

. 
. xtset PanelID MonthYear, monthly
       panel variable:  PanelID (unbalanced)
        time variable:  MonthYear, 2011m1 to 2016m12, but with gaps
                delta:  1 month

. xtnbreg Vehicle FergEff24 d.UnempL d.OffRateL d.DepScore d.PctNonWhtL  ///
> i.MonthYear if NoCov < 1, fe irr vce(bootstrap, seed(909) ///
> reps(5000) nodots) exposure(population)
note: 679.MonthYear omitted because of collinearity
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered

Conditional FE negative binomial regression     Number of obs     =      2,628
Group variable: PanelID                         Number of groups  =         44

                                                Obs per group:
                                                              min =         34
                                                              avg =       59.7
                                                              max =         71

                                                Wald chi2(74)     =   21115.04
Log likelihood  = -21157.609                    Prob > chi2       =     0.0000

                                (Replications based on 44 clusters in PanelID)
------------------------------------------------------------------------------
             |   Observed   Bootstrap                         Normal-based
     Vehicle |        IRR   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   FergEff24 |   .7717479   .0735284    -2.72   0.007     .6402904    .9301947
             |
      UnempL |
         D1. |   .8078829    .136642    -1.26   0.207     .5799355    1.125426
             |
    OffRateL |
         D1. |    .865894   .4135283    -0.30   0.763     .3395887    2.207884
             |
    DepScore |
         D1. |   .8658271   .0918398    -1.36   0.174     .7033034    1.065908
             |
  PctNonWhtL |
         D1. |   3.960634   8.238473     0.66   0.508     .0671722    233.5286
             |
   MonthYear |
        614  |    1.13772   .0392604     3.74   0.000     1.063316    1.217331
        615  |   1.008187   .0309486     0.27   0.791     .9493175    1.070707
        616  |   1.052747   .0431033     1.26   0.209      .971567     1.14071
        617  |    1.03748   .0383627     1.00   0.320     .9649509    1.115462
        618  |   1.010122   .0395243     0.26   0.797     .9355515    1.090636
        619  |   1.007454   .0527271     0.14   0.887     .9092348    1.116284
        620  |   .9403123   .0466543    -1.24   0.215     .8531769    1.036347
        621  |   .8796487   .0386979    -2.91   0.004     .8069801    .9588611
        622  |   .8685278   .0373989    -3.27   0.001     .7982352    .9450104
        623  |   .8450768   .0487215    -2.92   0.004      .754782    .9461735
        624  |   .9888625    .060869    -0.18   0.856     .8764771    1.115658
        625  |    .959473   .0546309    -0.73   0.467     .8581568    1.072751
        626  |   .9646506   .0656307    -0.53   0.597     .8442244    1.102255
        627  |   .8664902    .053083    -2.34   0.019      .768453    .9770348
        628  |   .9365163   .0590328    -1.04   0.298     .8276759    1.059669
        629  |   .8878245    .053107    -1.99   0.047     .7896066    .9982596
        630  |   .8806283    .049716    -2.25   0.024     .7883842    .9836652
        631  |   .9053779   .0559845    -1.61   0.108     .8020389    1.022032
        632  |   .8120518   .0493656    -3.42   0.001     .7208388    .9148067
        633  |   .8483217   .0498144    -2.80   0.005     .7560962    .9517965
        634  |    .832359   .0540593    -2.83   0.005     .7328711    .9453525
        635  |   .7612889   .0538307    -3.86   0.000     .6627672     .874456
        636  |   .9251685   .0631828    -1.14   0.255     .8092625    1.057675
        637  |   .8247738   .0575143    -2.76   0.006     .7194119    .9455665
        638  |   .9583707   .0655092    -0.62   0.534     .8382042    1.095765
        639  |   .8406354   .0572218    -2.55   0.011     .7356422    .9606137
        640  |   .8914091   .0599374    -1.71   0.087     .7813456    1.016977
        641  |   .8001216   .0520078    -3.43   0.001      .704414    .9088328
        642  |   .8080689   .0526347    -3.27   0.001     .7112205    .9181054
        643  |   .8679694   .0595192    -2.06   0.039     .7588135    .9928275
        644  |   .8069883   .0601156    -2.88   0.004     .6973616    .9338486
        645  |   .8642727   .0694403    -1.82   0.069     .7383474    1.011675
        646  |   .8376444   .0650492    -2.28   0.023     .7193789    .9753526
        647  |   .7730028   .0620807    -3.21   0.001     .6604199    .9047779
        648  |   .9110074   .0730604    -1.16   0.245     .7784986    1.066071
        649  |   .8690821   .0611516    -1.99   0.046     .7571246    .9975949
        650  |   .9142487   .0613696    -1.34   0.182     .8015431    1.042802
        651  |   .8744259   .0637786    -1.84   0.066     .7579462    1.008806
        652  |   .9042175   .0642457    -1.42   0.156     .7866726    1.039326
        653  |    .812122   .0540629    -3.13   0.002     .7127822    .9253068
        654  |   .8596311   .0543767    -2.39   0.017     .7593966    .9730958
        655  |   1.091234   .0942581     1.01   0.312     .9212834    1.292536
        656  |   1.027718   .0876206     0.32   0.748     .8695665    1.214634
        657  |   1.032634   .0892838     0.37   0.710     .8716647    1.223329
        658  |    .943817   .0789016    -0.69   0.489     .8011774    1.111852
        659  |   .8588557   .0745343    -1.75   0.080     .7245197      1.0181
        660  |   1.012297   .0875085     0.14   0.888     .8545264    1.199197
        661  |   .9583449   .0808089    -0.50   0.614     .8123579    1.130567
        662  |   1.031822    .085402     0.38   0.705      .877309    1.213549
        663  |   .9976548   .0906925    -0.03   0.979     .8348361    1.192228
        664  |   .9983389   .0819313    -0.02   0.984     .8500059    1.172557
        665  |   .9568546   .0758885    -0.56   0.578     .8190999    1.117777
        666  |   .9821945   .0852917    -0.21   0.836     .8284781    1.164432
        667  |   .9897185    .081538    -0.13   0.900      .842142    1.163156
        668  |   .9435707   .0730281    -0.75   0.453     .8107655     1.09813
        669  |   .9718879   .0698982    -0.40   0.692     .8441074    1.119012
        670  |    .919363   .0683587    -1.13   0.258     .7946875    1.063598
        671  |   .8750947   .0758429    -1.54   0.124      .738385    1.037116
        672  |    .998623   .0587877    -0.02   0.981     .8897999    1.120755
        673  |   1.019001    .047537     0.40   0.687      .929963    1.116564
        674  |   1.047796   .0474479     1.03   0.303     .9588077    1.145044
        675  |   .9298885   .0458535    -1.47   0.140     .8442237    1.024246
        676  |   .9969299    .057806    -0.05   0.958      .889833    1.116917
        677  |   .9791857   .0672101    -0.31   0.759     .8559327    1.120187
        678  |   .8875084   .0283862    -3.73   0.000     .8335805    .9449251
        679  |          1  (omitted)
        680  |   .7330456   .0714652    -3.19   0.001     .6055454    .8873917
        681  |   .6997381   .0781112    -3.20   0.001     .5622333    .8708722
        682  |   .6517807   .0743434    -3.75   0.000     .5212088    .8150631
        683  |   .6406032   .0767007    -3.72   0.000     .5066092    .8100377
             |
       _cons |   .0000407   8.17e-06   -50.38   0.000     .0000275    .0000604
ln(popula~n) |          1  (exposure)
------------------------------------------------------------------------------
Note: _cons estimates baseline incidence rate (conditional on zero random effects).
Note: One or more parameters could not be estimated in 45 bootstrap replicates;
      standard-error estimates include only complete replications.

. estat ic

Akaike's information criterion and Bayesian information criterion

-----------------------------------------------------------------------------
       Model |        Obs  ll(null)  ll(model)      df         AIC        BIC
-------------+---------------------------------------------------------------
           . |      2,628         .  -21157.61      75    42465.22   42905.77
-----------------------------------------------------------------------------
               Note: N=Obs used in calculating BIC; see [R] BIC note.

. 
. xtset PanelID MonthYear, monthly
       panel variable:  PanelID (unbalanced)
        time variable:  MonthYear, 2011m1 to 2016m12, but with gaps
                delta:  1 month

. xtnbreg Vehicle FergEff d.UnempL d.OffRateL d.DepScore d.PctNonWhtL  ///
> i.MonthYear if NoCov < 1, fe irr vce(bootstrap, seed(909) ///
> reps(5000) nodots) exposure(population)
note: 683.MonthYear omitted because of collinearity
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered

Conditional FE negative binomial regression     Number of obs     =      2,628
Group variable: PanelID                         Number of groups  =         44

                                                Obs per group:
                                                              min =         34
                                                              avg =       59.7
                                                              max =         71

                                                Wald chi2(74)     =   21179.93
Log likelihood  = -21157.609                    Prob > chi2       =     0.0000

                                (Replications based on 44 clusters in PanelID)
------------------------------------------------------------------------------
             |   Observed   Bootstrap                         Normal-based
     Vehicle |        IRR   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     FergEff |   .6406032   .0767097    -3.72   0.000     .5065953    .8100599
             |
      UnempL |
         D1. |   .8078829   .1366151    -1.26   0.207     .5799733    1.125353
             |
    OffRateL |
         D1. |   .8658939   .4128986    -0.30   0.763     .3400729    2.204739
             |
    DepScore |
         D1. |   .8658271   .0918994    -1.36   0.175     .7032085    1.066052
             |
  PctNonWhtL |
         D1. |   3.960632    8.23959     0.66   0.508     .0671349    233.6581
             |
   MonthYear |
        614  |    1.13772   .0391834     3.75   0.000     1.063457     1.21717
        615  |   1.008187    .030908     0.27   0.790     .9493924    1.070622
        616  |   1.052747   .0430497     1.26   0.209     .9716639    1.140596
        617  |    1.03748   .0383508     1.00   0.320     .9649726    1.115437
        618  |   1.010122   .0394823     0.26   0.797     .9356278    1.090547
        619  |   1.007454   .0526416     0.14   0.887      .909386    1.116098
        620  |   .9403123   .0465739    -1.24   0.214     .8533199    1.036173
        621  |   .8796487   .0386609    -2.92   0.004     .8070467     .958782
        622  |   .8685278     .03733    -3.28   0.001     .7983592    .9448635
        623  |   .8450768    .048721    -2.92   0.004     .7547829    .9461724
        624  |   .9888625   .0608538    -0.18   0.856     .8765035    1.115625
        625  |    .959473   .0546034    -0.73   0.467      .858205    1.072691
        626  |   .9646506   .0655806    -0.53   0.597     .8443105    1.102143
        627  |   .8664902   .0530434    -2.34   0.019     .7685217    .9769474
        628  |   .9365163   .0589921    -1.04   0.298     .8277465    1.059579
        629  |   .8878245   .0530841    -1.99   0.047     .7896466    .9982091
        630  |   .8806283   .0497004    -2.25   0.024     .7884116    .9836311
        631  |   .9053779   .0559595    -1.61   0.108     .8020822    1.021976
        632  |   .8120518   .0493103    -3.43   0.001      .720935    .9146846
        633  |   .8483217     .04977    -2.80   0.005     .7561738    .9516988
        634  |    .832359   .0540138    -2.83   0.005     .7329496    .9452512
        635  |   .7612889    .053837    -3.86   0.000     .6627565    .8744701
        636  |   .9251685   .0631328    -1.14   0.254     .8093483    1.057563
        637  |   .8247738   .0574029    -2.77   0.006     .7196024    .9453162
        638  |   .9583707   .0654402    -0.62   0.533     .8383225     1.09561
        639  |   .8406354    .057192    -2.55   0.011     .7356934    .9605468
        640  |   .8914091   .0598718    -1.71   0.087     .7814584     1.01683
        641  |   .8001216   .0519694    -3.43   0.001     .7044803    .9087473
        642  |   .8080689   .0525851    -3.27   0.001     .7113059    .9179951
        643  |   .8679694   .0594794    -2.07   0.039     .7588817    .9927384
        644  |   .8069883   .0601019    -2.88   0.004     .6973848    .9338175
        645  |   .8642727   .0694262    -1.82   0.069     .7383709    1.011642
        646  |   .8376443   .0650689    -2.28   0.023     .7193456    .9753976
        647  |   .7730027   .0621207    -3.20   0.001     .6603528    .9048697
        648  |   .9110074   .0730478    -1.16   0.245     .7785195    1.066042
        649  |   .8690821   .0610523    -2.00   0.046     .7572941    .9973716
        650  |   .9142487   .0612218    -1.34   0.181     .8017971    1.042472
        651  |   .8744259    .063708    -1.84   0.066      .758066    1.008647
        652  |   .9042175   .0641233    -1.42   0.156     .7868814     1.03905
        653  |    .812122   .0539947    -3.13   0.002     .7128996    .9251544
        654  |   .8596311   .0543329    -2.39   0.017     .7594724    .9729985
        655  |   1.314632   .1615448     2.23   0.026     1.033253    1.672637
        656  |   1.238113   .1493818     1.77   0.077     .9773735    1.568412
        657  |   1.244035   .1465331     1.85   0.064     .9875765    1.567092
        658  |   1.137036   .1228134     1.19   0.234     .9200983    1.405122
        659  |   1.034681   .1123405     0.31   0.754     .8363487    1.280046
        660  |   1.219535   .1325165     1.83   0.068     .9856017    1.508993
        661  |   1.154538   .1318223     1.26   0.208     .9230389    1.444097
        662  |   1.243058   .1337621     2.02   0.043      1.00669    1.534924
        663  |   1.201895   .1338217     1.65   0.099     .9662554       1.495
        664  |   1.202719   .1228023     1.81   0.071     .9845853    1.469181
        665  |   1.152742   .1145414     1.43   0.153     .9487532    1.400591
        666  |    1.18327   .1248046     1.60   0.111     .9622855    1.455002
        667  |   1.192334   .1329363     1.58   0.115     .9582866    1.483544
        668  |   1.136739    .121213     1.20   0.229     .9223489    1.400962
        669  |   1.170853   .1147541     1.61   0.108     .9662224    1.418822
        670  |   1.107575   .1081893     1.05   0.296      .914591    1.341281
        671  |   1.054244   .1129776     0.49   0.622      .854521    1.300648
        672  |   1.203062   .1011456     2.20   0.028     1.020292    1.418572
        673  |   1.227612   .0819646     3.07   0.002     1.077031    1.399245
        674  |   1.262302   .0787542     3.73   0.000     1.117011    1.426491
        675  |   1.120256   .0594406     2.14   0.032     1.009608    1.243031
        676  |   1.201022   .0694945     3.17   0.002     1.072255    1.345253
        677  |   1.179645   .0748014     2.61   0.009     1.041781    1.335753
        678  |     1.0692    .056581     1.26   0.206     .9638602    1.186051
        679  |   1.204721   .0735222     3.05   0.002     1.068904    1.357794
        680  |   1.144305   .0659745     2.34   0.019     1.022036    1.281202
        681  |   1.092311   .0487927     1.98   0.048     1.000746    1.192254
        682  |   1.017448   .0393071     0.45   0.654     .9432522    1.097481
        683  |          1  (omitted)
             |
       _cons |   .0000407   8.17e-06   -50.41   0.000     .0000275    .0000603
ln(popula~n) |          1  (exposure)
------------------------------------------------------------------------------
Note: _cons estimates baseline incidence rate (conditional on zero random effects).
Note: One or more parameters could not be estimated in 34 bootstrap replicates;
      standard-error estimates include only complete replications.

. estat ic

Akaike's information criterion and Bayesian information criterion

-----------------------------------------------------------------------------
       Model |        Obs  ll(null)  ll(model)      df         AIC        BIC
-------------+---------------------------------------------------------------
           . |      2,628         .  -21157.61      75    42465.22   42905.77
-----------------------------------------------------------------------------
               Note: N=Obs used in calculating BIC; see [R] BIC note.

. 
. * Pedestrian Stops
. xtset PanelID MonthYear, monthly
       panel variable:  PanelID (unbalanced)
        time variable:  MonthYear, 2011m1 to 2016m12, but with gaps
                delta:  1 month

. xtnbreg Ped FergEff1 d.UnempL d.OffRateL d.DepScore d.PctNonWhtL  ///
> i.MonthYear if NoCov < 1 & Ped > 0 & weirdPed < 1, fe irr vce(bootstrap, seed(909) ///
> reps(5000) nodots) exposure(population)
note: 655.MonthYear omitted because of collinearity
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered

Conditional FE negative binomial regression     Number of obs     =      1,120
Group variable: PanelID                         Number of groups  =         19

                                                Obs per group:
                                                              min =         15
                                                              avg =       58.9
                                                              max =         71

                                                Wald chi2(74)     =   54014.70
Log likelihood  = -6590.7145                    Prob > chi2       =     0.0000

                                (Replications based on 19 clusters in PanelID)
------------------------------------------------------------------------------
             |   Observed   Bootstrap                         Normal-based
         Ped |        IRR   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    FergEff1 |   1.229729   .2752806     0.92   0.356     .7929831    1.907018
             |
      UnempL |
         D1. |   .1852778   .1996177    -1.56   0.118     .0224255    1.530753
             |
    OffRateL |
         D1. |   .8001054   .3858649    -0.46   0.644      .310914     2.05899
             |
    DepScore |
         D1. |   2.245577   1.210186     1.50   0.133     .7809056    6.457394
             |
  PctNonWhtL |
         D1. |   19646.06   230076.8     0.84   0.399     2.11e-06    1.83e+14
             |
   MonthYear |
        614  |    1.28728   .1019919     3.19   0.001     1.102128    1.503537
        615  |   1.098762   .0619299     1.67   0.095     .9838459      1.2271
        616  |   1.323266     .13591     2.73   0.006     1.081987    1.618349
        617  |   1.370403   .1931278     2.24   0.025     1.039658    1.806368
        618  |   1.289691   .2073073     1.58   0.113     .9411568    1.767296
        619  |   1.251686   .2055633     1.37   0.172     .9072004    1.726981
        620  |   1.199413   .1548464     1.41   0.159     .9312731    1.544758
        621  |   1.141257   .1524047     0.99   0.322     .8784417    1.482701
        622  |   1.001441   .1264674     0.01   0.991      .781864    1.282684
        623  |    .947486   .1423389    -0.36   0.720     .7058274    1.271883
        624  |   1.153128   .2528596     0.65   0.516     .7502828    1.772272
        625  |   .8617436   .2593068    -0.49   0.621     .4777971    1.554221
        626  |   1.168821   .2214708     0.82   0.410     .8062328    1.694476
        627  |   1.123414   .1817286     0.72   0.472     .8181737    1.542532
        628  |   1.135869   .2602165     0.56   0.578     .7249802    1.779632
        629  |   1.197132   .1964105     1.10   0.273     .8679354    1.651188
        630  |    1.22305   .2457538     1.00   0.316     .8249125    1.813346
        631  |   1.083245   .2255864     0.38   0.701     .7202171    1.629258
        632  |   1.080216   .1784505     0.47   0.640     .7814355    1.493235
        633  |   .9807154   .2535551    -0.08   0.940     .5908435    1.627847
        634  |   .8160502   .2444289    -0.68   0.497     .4536901    1.467826
        635  |   .8439004   .2337901    -0.61   0.540     .4903187    1.452459
        636  |   1.097564   .3012703     0.34   0.734     .6408899    1.879646
        637  |    .743274   .1884108    -1.17   0.242     .4522513    1.221569
        638  |   .9960564   .2701769    -0.01   0.988     .5853268    1.694999
        639  |   1.034509   .2249639     0.16   0.876     .6755104    1.584295
        640  |    1.22713   .2656277     0.95   0.344      .802855    1.875615
        641  |   1.428054   .3802179     1.34   0.181     .8474485    2.406447
        642  |   1.157937   .2639121     0.64   0.520     .7407686    1.810036
        643  |   .9725745   .2535155    -0.11   0.915     .5835055    1.621066
        644  |   .9450706   .2283596    -0.23   0.815     .5885542    1.517547
        645  |   1.018408    .251692     0.07   0.941     .6274129    1.653065
        646  |   .8006981   .2432077    -0.73   0.464       .44149    1.452167
        647  |   .6673541   .2351084    -1.15   0.251     .3345636    1.331172
        648  |   .9260579   .3414078    -0.21   0.835     .4496013    1.907431
        649  |   .7120147    .229363    -1.05   0.292     .3786948    1.338716
        650  |   .7822654   .2326743    -0.83   0.409     .4366924    1.401305
        651  |   .7467399   .2341488    -0.93   0.352     .4038921    1.380617
        652  |   1.014989    .252576     0.06   0.952     .6232229    1.653026
        653  |   1.078904   .2254018     0.36   0.716     .7163941    1.624851
        654  |   1.433003   .4037468     1.28   0.202     .8249393     2.48927
        655  |          1  (omitted)
        656  |   1.147432   .2827186     0.56   0.577     .7079414    1.859759
        657  |   .8578515   .2061879    -0.64   0.524     .5355778    1.374047
        658  |   .6763115    .163181    -1.62   0.105     .4214715    1.085239
        659  |   .6300264   .1426087    -2.04   0.041     .4042838    .9818185
        660  |    1.05621   .2912311     0.20   0.843     .6152428    1.813234
        661  |   .6276053    .179453    -1.63   0.103     .3583439    1.099191
        662  |   .7071687   .1892121    -1.29   0.195     .4185748    1.194739
        663  |   .7843217   .1684159    -1.13   0.258     .5148935    1.194734
        664  |   1.219246   .3178638     0.76   0.447     .7314397    2.032376
        665  |   1.163223   .2973874     0.59   0.554     .7047679    1.919904
        666  |   1.173355   .3225891     0.58   0.561     .6845569    2.011172
        667  |   1.006128     .19071     0.03   0.974       .69392    1.458805
        668  |   .7445572   .1825424    -1.20   0.229     .4604789    1.203889
        669  |   .8220057   .1843644    -0.87   0.382     .5296174    1.275814
        670  |   .7030015   .1553048    -1.60   0.111      .455944    1.083929
        671  |   .5908004   .1169634    -2.66   0.008     .4007972    .8708771
        672  |   1.065433   .3881753     0.17   0.862     .5216787    2.175952
        673  |   .6158583   .1697851    -1.76   0.079     .3587685    1.057176
        674  |   .7301039   .1747545    -1.31   0.189     .4567144    1.167144
        675  |    .638449    .164336    -1.74   0.081     .3855031    1.057364
        676  |   .6947131   .1681249    -1.51   0.132     .4323241    1.116353
        677  |   .9651731   .2501681    -0.14   0.891      .580735    1.604104
        678  |   .9777464   .3221702    -0.07   0.946     .5125696    1.865089
        679  |   .6925408   .1745962    -1.46   0.145      .422522    1.135119
        680  |   .8464601    .218385    -0.65   0.518     .5105029    1.403507
        681  |   .5852771   .1417044    -2.21   0.027     .3641437    .9406981
        682  |   .4835249   .1119565    -3.14   0.002     .3071352    .7612162
        683  |   .5325497   .1158064    -2.90   0.004      .347745    .8155666
             |
       _cons |   9.65e-06   6.21e-06   -17.95   0.000     2.73e-06    .0000341
ln(popula~n) |          1  (exposure)
------------------------------------------------------------------------------
Note: _cons estimates baseline incidence rate (conditional on zero random effects).
Note: One or more parameters could not be estimated in 14 bootstrap replicates;
      standard-error estimates include only complete replications.

. estat ic

Akaike's information criterion and Bayesian information criterion

-----------------------------------------------------------------------------
       Model |        Obs  ll(null)  ll(model)      df         AIC        BIC
-------------+---------------------------------------------------------------
           . |      1,120         .  -6590.714      75    13331.43   13708.01
-----------------------------------------------------------------------------
               Note: N=Obs used in calculating BIC; see [R] BIC note.

. 
. xtset PanelID MonthYear, monthly
       panel variable:  PanelID (unbalanced)
        time variable:  MonthYear, 2011m1 to 2016m12, but with gaps
                delta:  1 month

. xtnbreg Ped FergEff6 d.UnempL d.OffRateL d.DepScore d.PctNonWhtL  ///
> i.MonthYear if NoCov < 1 & Ped > 0 & weirdPed < 1, fe irr vce(bootstrap, seed(909) ///
> reps(5000) nodots) exposure(population)
note: 661.MonthYear omitted because of collinearity
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered

Conditional FE negative binomial regression     Number of obs     =      1,120
Group variable: PanelID                         Number of groups  =         19

                                                Obs per group:
                                                              min =         15
                                                              avg =       58.9
                                                              max =         71

                                                Wald chi2(74)     =   53973.38
Log likelihood  = -6590.7145                    Prob > chi2       =     0.0000

                                (Replications based on 19 clusters in PanelID)
------------------------------------------------------------------------------
             |   Observed   Bootstrap                         Normal-based
         Ped |        IRR   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    FergEff6 |   .6276053   .1795456    -1.63   0.103     .3582403    1.099509
             |
      UnempL |
         D1. |   .1852779   .1996449    -1.56   0.118     .0224191    1.531193
             |
    OffRateL |
         D1. |   .8001059   .3859004    -0.46   0.644     .3108873    2.059169
             |
    DepScore |
         D1. |   2.245563   1.211146     1.50   0.134     .7802412    6.462812
             |
  PctNonWhtL |
         D1. |   19651.26     229972     0.84   0.398     2.15e-06    1.80e+14
             |
   MonthYear |
        614  |    1.28728   .1019678     3.19   0.001     1.102168    1.503482
        615  |   1.098762   .0619128     1.67   0.095     .9838758    1.227063
        616  |   1.323266   .1355879     2.73   0.006     1.082503    1.617577
        617  |   1.370403   .1928309     2.24   0.025     1.040099    1.805601
        618  |   1.289691   .2070968     1.58   0.113     .9414579    1.766731
        619  |   1.251686    .205356     1.37   0.171     .9074949     1.72642
        620  |   1.199413   .1546213     1.41   0.158     .9316156     1.54419
        621  |   1.141257   .1522054     0.99   0.322     .8787423    1.482194
        622  |   1.001441   .1263759     0.01   0.991      .782004    1.282455
        623  |    .947486   .1423441    -0.36   0.720     .7058198    1.271897
        624  |   1.153127   .2527258     0.65   0.516     .7504527    1.771868
        625  |   .8617436   .2592961    -0.49   0.621     .4778087    1.554183
        626  |   1.168821   .2214174     0.82   0.410      .806305    1.694325
        627  |   1.123414   .1816752     0.72   0.472     .8182499    1.542388
        628  |   1.135869   .2602656     0.56   0.578     .7249189    1.779782
        629  |   1.197132   .1964174     1.10   0.273     .8679254    1.651206
        630  |    1.22305   .2458256     1.00   0.316     .8248176    1.813554
        631  |   1.083245   .2256494     0.38   0.701     .7201351    1.629444
        632  |   1.080216   .1784343     0.47   0.640     .7814586    1.493191
        633  |   .9807154   .2536857    -0.08   0.940     .5906894    1.628271
        634  |   .8160502   .2444691    -0.68   0.497     .4536462    1.467968
        635  |   .8439004   .2338559    -0.61   0.540     .4902437    1.452681
        636  |   1.097563    .301261     0.34   0.734     .6409002    1.879615
        637  |    .743274   .1884769    -1.17   0.242     .4521725    1.221782
        638  |   .9960564   .2702946    -0.01   0.988     .5851913    1.695392
        639  |   1.034509   .2250148     0.16   0.876     .6754453    1.584448
        640  |    1.22713   .2657728     0.95   0.345      .802669     1.87605
        641  |   1.428054    .380224     1.34   0.181     .8474413    2.406467
        642  |   1.157937   .2640263     0.64   0.520     .7406254    1.810386
        643  |   .9725745   .2536073    -0.11   0.915     .5833977    1.621366
        644  |   .9450707   .2285347    -0.23   0.815     .5883405    1.518098
        645  |   1.018408   .2519445     0.07   0.941      .627108    1.653868
        646  |   .8006981   .2432961    -0.73   0.464     .4413946    1.452481
        647  |   .6673541   .2352375    -1.15   0.251     .3344367    1.331676
        648  |   .9260566   .3414891    -0.21   0.835     .4495228    1.907758
        649  |   .7120147   .2295001    -1.05   0.292      .378552    1.339221
        650  |   .7822654   .2327388    -0.83   0.409     .4366219    1.401531
        651  |     .74674   .2342311    -0.93   0.352      .403805    1.380916
        652  |   1.014989   .2527585     0.06   0.952     .6230033    1.653608
        653  |   1.078904   .2255064     0.36   0.716     .7162579     1.62516
        654  |   1.433003   .4038748     1.28   0.202     .8247948    2.489706
        655  |   1.959399   .5639358     2.34   0.019     1.114649    3.444353
        656  |    1.82827   .5859108     1.88   0.060     .9755589    3.426315
        657  |   1.366865   .1224991     3.49   0.000     1.146675    1.629336
        658  |   1.077606   .0805309     1.00   0.317     .9307839    1.247589
        659  |   1.003858   .0938551     0.04   0.967     .8357754    1.205743
        660  |   1.682917   .4134357     2.12   0.034     1.039803    2.723793
        661  |          1  (omitted)
        662  |   .7071687    .189326    -1.29   0.196     .4184427    1.195116
        663  |   .7843217   .1685115    -1.13   0.258     .5147705    1.195019
        664  |   1.219246    .317694     0.76   0.447     .7316394    2.031821
        665  |   1.163223   .2972555     0.59   0.554     .7049246    1.919477
        666  |   1.173355   .3224276     0.58   0.561     .6847416     2.01063
        667  |   1.006128    .190625     0.03   0.974     .6940351    1.458563
        668  |   .7445572   .1827037    -1.20   0.229     .4602835      1.2044
        669  |   .8220057   .1845021    -0.87   0.383     .5294435    1.276233
        670  |   .7030015    .155411    -1.59   0.111     .4558091     1.08425
        671  |   .5908004   .1170392    -2.66   0.008     .4006964    .8710962
        672  |    1.06543   .3882254     0.17   0.862     .5216281    2.176151
        673  |   .6158583   .1698942    -1.76   0.079     .3586439    1.057543
        674  |   .7301039   .1748158    -1.31   0.189     .4566393    1.167336
        675  |    .638449   .1644345    -1.74   0.081     .3853866    1.057684
        676  |   .6947131   .1682218    -1.50   0.133     .4322058    1.116658
        677  |    .965173   .2501316    -0.14   0.891     .5807779    1.603985
        678  |   .9777463   .3221263    -0.07   0.946     .5126147    1.864925
        679  |   .6925408   .1746344    -1.46   0.145     .4224763    1.135242
        680  |   .8464601   .2183485    -0.65   0.518      .510546    1.403389
        681  |   .5852771   .1417739    -2.21   0.027      .364059     .940917
        682  |   .4835249   .1120137    -3.14   0.002     .3070641    .7613927
        683  |   .5325497   .1158314    -2.90   0.004      .347713    .8156416
             |
       _cons |   9.65e-06   6.21e-06   -17.95   0.000     2.73e-06    .0000341
ln(popula~n) |          1  (exposure)
------------------------------------------------------------------------------
Note: _cons estimates baseline incidence rate (conditional on zero random effects).
Note: One or more parameters could not be estimated in 14 bootstrap replicates;
      standard-error estimates include only complete replications.

. estat ic

Akaike's information criterion and Bayesian information criterion

-----------------------------------------------------------------------------
       Model |        Obs  ll(null)  ll(model)      df         AIC        BIC
-------------+---------------------------------------------------------------
           . |      1,120         .  -6590.714      75    13331.43   13708.01
-----------------------------------------------------------------------------
               Note: N=Obs used in calculating BIC; see [R] BIC note.

. 
. xtset PanelID MonthYear, monthly
       panel variable:  PanelID (unbalanced)
        time variable:  MonthYear, 2011m1 to 2016m12, but with gaps
                delta:  1 month

. xtnbreg Ped FergEff12 d.UnempL d.OffRateL d.DepScore d.PctNonWhtL  ///
> i.MonthYear if NoCov < 1 & Ped > 0 & weirdPed < 1, fe irr vce(bootstrap, seed(909) ///
> reps(5000) nodots) exposure(population)
note: 667.MonthYear omitted because of collinearity
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered

Conditional FE negative binomial regression     Number of obs     =      1,120
Group variable: PanelID                         Number of groups  =         19

                                                Obs per group:
                                                              min =         15
                                                              avg =       58.9
                                                              max =         71

                                                Wald chi2(74)     =   53698.35
Log likelihood  = -6590.7145                    Prob > chi2       =     0.0000

                                (Replications based on 19 clusters in PanelID)
------------------------------------------------------------------------------
             |   Observed   Bootstrap                         Normal-based
         Ped |        IRR   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   FergEff12 |   1.006128   .1907172     0.03   0.974     .6939099    1.458825
             |
      UnempL |
         D1. |   .1852777   .1997251    -1.56   0.118        .0224    1.532494
             |
    OffRateL |
         D1. |   .8001071   .3862073    -0.46   0.644     .3106546    2.060718
             |
    DepScore |
         D1. |   2.245581   1.211295     1.50   0.134     .7801532    6.463646
             |
  PctNonWhtL |
         D1. |   19646.01   230007.7     0.84   0.398     2.13e-06    1.81e+14
             |
   MonthYear |
        614  |    1.28728   .1019966     3.19   0.001      1.10212    1.503548
        615  |   1.098762   .0619325     1.67   0.095     .9838409    1.227106
        616  |   1.323265    .135829     2.73   0.006     1.082116    1.618155
        617  |   1.370403   .1930402     2.24   0.025     1.039788    1.806142
        618  |   1.289691   .2070466     1.58   0.113     .9415295    1.766596
        619  |   1.251686   .2053958     1.37   0.171     .9074381    1.726527
        620  |   1.199413   .1547051     1.41   0.159     .9314879    1.544401
        621  |   1.141256    .152245     0.99   0.322     .8786824    1.482295
        622  |   1.001441   .1264522     0.01   0.991     .7818871    1.282646
        623  |    .947486   .1424156    -0.36   0.720     .7057154    1.272085
        624  |   1.153128    .252692     0.65   0.516     .7504962    1.771767
        625  |   .8617433   .2593752    -0.49   0.621     .4777225    1.554462
        626  |    1.16882   .2214475     0.82   0.410     .8062637     1.69441
        627  |   1.123413   .1817459     0.72   0.472     .8181486    1.542578
        628  |   1.135868   .2603801     0.56   0.578     .7247752    1.780134
        629  |   1.197131   .1964172     1.10   0.273     .8679253    1.651206
        630  |    1.22305   .2458925     1.00   0.317     .8247288    1.813748
        631  |   1.083245   .2256755     0.38   0.701     .7201006    1.629521
        632  |   1.080216   .1785002     0.47   0.641     .7813646     1.49337
        633  |    .980715   .2537166    -0.08   0.940     .5906526    1.628372
        634  |   .8160499    .244465    -0.68   0.497     .4536504    1.467953
        635  |   .8439003   .2338458    -0.61   0.540     .4902552    1.452647
        636  |   1.097563   .3011869     0.34   0.734      .640985    1.879366
        637  |   .7432737   .1885102    -1.17   0.242     .4521326    1.221889
        638  |    .996056   .2703634    -0.01   0.988     .5851117    1.695621
        639  |   1.034508   .2251231     0.16   0.876     .6753064    1.584773
        640  |   1.227129   .2658511     0.94   0.345     .8025682    1.876284
        641  |   1.428054   .3803696     1.34   0.181     .8472716    2.406947
        642  |   1.157936    .264105     0.64   0.520     .7405263    1.810626
        643  |   .9725741   .2536825    -0.11   0.915     .5833088    1.621612
        644  |   .9450702   .2286203    -0.23   0.815     .5882358    1.518367
        645  |   1.018407   .2519794     0.07   0.941     .6270655    1.653979
        646  |   .8006978   .2433615    -0.73   0.465     .4413236    1.452714
        647  |   .6673546   .2353166    -1.15   0.251     .3343594    1.331986
        648  |   .9260591   .3416062    -0.21   0.835     .4494135    1.908233
        649  |   .7120144   .2295763    -1.05   0.292     .3784723    1.339502
        650  |    .782265   .2328114    -0.83   0.409     .4365422    1.401786
        651  |   .7467396   .2343348    -0.93   0.352     .4036947    1.381291
        652  |   1.014989   .2528673     0.06   0.952     .6228721    1.653955
        653  |   1.078903    .225564     0.36   0.716     .7161826     1.62533
        654  |   1.433002   .4040093     1.28   0.202     .8246427    2.490163
        655  |   1.222239   .1392317     1.76   0.078     .9776676    1.527992
        656  |   1.140443   .1310143     1.14   0.253     .9105157    1.428433
        657  |   .8526264   .2312085    -0.59   0.557     .5011141    1.450711
        658  |   .6721922   .1869846    -1.43   0.153     .3896849    1.159507
        659  |    .626189   .1728595    -1.70   0.090     .3645282    1.075671
        660  |   1.049777   .2334877     0.22   0.827     .6788531    1.623373
        661  |   .6237826   .1963035    -1.50   0.134     .3366366     1.15586
        662  |   .7028614   .2129362    -1.16   0.244      .388144     1.27276
        663  |   .7795444   .1717477    -1.13   0.258      .506181    1.200538
        664  |   1.211819   .1491982     1.56   0.119     .9520038    1.542543
        665  |   1.156137   .1305852     1.28   0.199     .9265453    1.442621
        666  |   1.166208     .15163     1.18   0.237      .903864    1.504697
        667  |          1  (omitted)
        668  |   .7445569   .1827584    -1.20   0.229     .4602169    1.204573
        669  |   .8220054   .1845115    -0.87   0.383     .5294313    1.276262
        670  |   .7030012   .1554142    -1.59   0.111     .4558048    1.084259
        671  |   .5908001   .1170544    -2.66   0.008     .4006759    .8711401
        672  |   1.065434   .3882624     0.17   0.862     .5215954    2.176301
        673  |    .615858   .1699303    -1.76   0.079     .3586025    1.057665
        674  |   .7301035   .1748542    -1.31   0.189     .4565919    1.167456
        675  |   .6384487    .164471    -1.74   0.082     .3853432    1.057802
        676  |   .6947127   .1683137    -1.50   0.133     .4320935    1.116948
        677  |   .9651727   .2501653    -0.14   0.891     .5807379    1.604094
        678  |   .9777461   .3222497    -0.07   0.946     .5124877    1.865386
        679  |   .6925405   .1746177    -1.46   0.145      .422496    1.135188
        680  |   .8464597   .2183987    -0.65   0.518     .5104863    1.403552
        681  |   .5852768   .1417584    -2.21   0.027     .3640777    .9408679
        682  |   .4835247   .1120187    -3.14   0.002     .3070575    .7614081
        683  |   .5325495   .1158106    -2.90   0.004     .3477393    .8155792
             |
       _cons |   9.65e-06   6.21e-06   -17.94   0.000     2.73e-06    .0000341
ln(popula~n) |          1  (exposure)
------------------------------------------------------------------------------
Note: _cons estimates baseline incidence rate (conditional on zero random effects).
Note: One or more parameters could not be estimated in 16 bootstrap replicates;
      standard-error estimates include only complete replications.

. estat ic

Akaike's information criterion and Bayesian information criterion

-----------------------------------------------------------------------------
       Model |        Obs  ll(null)  ll(model)      df         AIC        BIC
-------------+---------------------------------------------------------------
           . |      1,120         .  -6590.714      75    13331.43   13708.01
-----------------------------------------------------------------------------
               Note: N=Obs used in calculating BIC; see [R] BIC note.

. 
. xtset PanelID MonthYear, monthly
       panel variable:  PanelID (unbalanced)
        time variable:  MonthYear, 2011m1 to 2016m12, but with gaps
                delta:  1 month

. xtnbreg Ped FergEff18 d.UnempL d.OffRateL d.DepScore d.PctNonWhtL  ///
> i.MonthYear if NoCov < 1 & Ped > 0 & weirdPed < 1, fe irr vce(bootstrap, seed(909) ///
> reps(5000) nodots) exposure(population)
note: 673.MonthYear omitted because of collinearity
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered

Conditional FE negative binomial regression     Number of obs     =      1,120
Group variable: PanelID                         Number of groups  =         19

                                                Obs per group:
                                                              min =         15
                                                              avg =       58.9
                                                              max =         71

                                                Wald chi2(74)     =   54023.71
Log likelihood  = -6590.7145                    Prob > chi2       =     0.0000

                                (Replications based on 19 clusters in PanelID)
------------------------------------------------------------------------------
             |   Observed   Bootstrap                         Normal-based
         Ped |        IRR   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   FergEff18 |   .6158582   .1698851    -1.76   0.079     .3586543    1.057513
             |
      UnempL |
         D1. |   .1852777   .1997866    -1.56   0.118     .0223854    1.533491
             |
    OffRateL |
         D1. |   .8001053   .3857651    -0.46   0.644     .3109899    2.058486
             |
    DepScore |
         D1. |   2.245577   1.210795     1.50   0.134      .780491    6.460828
             |
  PctNonWhtL |
         D1. |   19645.88   230022.6     0.84   0.398     2.12e-06    1.82e+14
             |
   MonthYear |
        614  |    1.28728   .1019623     3.19   0.001     1.102178     1.50347
        615  |   1.098762   .0619613     1.67   0.095     .9837907    1.227169
        616  |   1.323266   .1354693     2.74   0.006     1.082693    1.617293
        617  |   1.370403   .1928888     2.24   0.025     1.040014    1.805751
        618  |   1.289691   .2071282     1.58   0.113     .9414131    1.766815
        619  |   1.251686   .2051295     1.37   0.171     .9078169    1.725808
        620  |   1.199413   .1547609     1.41   0.159     .9314032    1.544542
        621  |   1.141257   .1522955     0.99   0.322     .8786064    1.482424
        622  |   1.001441   .1264343     0.01   0.991     .7819145    1.282601
        623  |    .947486   .1424653    -0.36   0.720     .7056429    1.272215
        624  |   1.153128   .2530232     0.65   0.516     .7500742    1.772765
        625  |   .8617437   .2593847    -0.49   0.621     .4777125    1.554496
        626  |   1.168821   .2214472     0.82   0.410     .8062646    1.694409
        627  |   1.123414   .1817878     0.72   0.472     .8180891    1.542691
        628  |   1.135869   .2603568     0.56   0.578     .7248049    1.780063
        629  |   1.197132   .1964989     1.10   0.273     .8678097    1.651427
        630  |    1.22305   .2459035     1.00   0.317     .8247146    1.813781
        631  |   1.083245   .2257629     0.38   0.701     .7199871    1.629778
        632  |   1.080216   .1786372     0.47   0.641     .7811708    1.493741
        633  |   .9807155   .2538081    -0.08   0.940     .5905451     1.62867
        634  |   .8160503   .2445828    -0.68   0.498     .4535224    1.468369
        635  |   .8439004   .2339331    -0.61   0.540     .4901558    1.452942
        636  |   1.097564   .3013894     0.34   0.735     .6407537    1.880046
        637  |    .743274   .1885622    -1.17   0.242     .4520708    1.222057
        638  |   .9960564    .270402    -0.01   0.988     .5850676     1.69575
        639  |   1.034509   .2251802     0.16   0.876     .6752336    1.584945
        640  |    1.22713   .2660959     0.94   0.345     .8022549    1.877018
        641  |   1.428054   .3806191     1.34   0.181     .8469819    2.407772
        642  |   1.157937   .2641991     0.64   0.520     .7404087    1.810915
        643  |   .9725746   .2536874    -0.11   0.915     .5833036    1.621628
        644  |   .9450708   .2286077    -0.23   0.815     .5882516    1.518328
        645  |   1.018408   .2520529     0.07   0.941     .6269774    1.654213
        646  |   .8006981   .2433714    -0.73   0.465     .4413132    1.452749
        647  |   .6673541   .2352734    -1.15   0.251     .3344014    1.331817
        648  |    .926058   .3416512    -0.21   0.835     .4493698    1.908414
        649  |   .7120146   .2294987    -1.05   0.292     .3785533    1.339217
        650  |   .7822653   .2327862    -0.83   0.409     .4365699    1.401698
        651  |   .7467398   .2342898    -0.93   0.352     .4037426    1.381128
        652  |   1.014989   .2527996     0.06   0.952     .6229539    1.653739
        653  |   1.078904   .2255843     0.36   0.716     .7161565     1.62539
        654  |   1.433003   .4041442     1.28   0.202     .8244911    2.490623
        655  |   1.996773   .4857298     2.84   0.004      1.23956    3.216546
        656  |   1.863143   .5083734     2.28   0.023     1.091413    3.180558
        657  |   1.392937   .1035421     4.46   0.000     1.204088    1.611403
        658  |   1.098161   .0766493     1.34   0.180     .9577539    1.259152
        659  |   1.023005   .1139999     0.20   0.838     .8222867    1.272719
        660  |   1.715021   .3642075     2.54   0.011     1.131112     2.60036
        661  |   1.019074   .0685916     0.28   0.779     .8931273    1.162782
        662  |   1.148265   .0841572     1.89   0.059     .9946197    1.325645
        663  |   1.273542   .1199742     2.57   0.010     1.058829    1.531796
        664  |   1.979751   .6965904     1.94   0.052     .9933647    3.945593
        665  |   1.888783   .6708939     1.79   0.073      .941534     3.78903
        666  |   1.905235   .6980196     1.76   0.079     .9291686    3.906633
        667  |   1.633701   .4566123     1.76   0.079      .944638    2.825398
        668  |   1.208975   .1214015     1.89   0.059      .992984    1.471947
        669  |   1.334732   .0935362     4.12   0.000     1.163437    1.531247
        670  |   1.141499   .0889586     1.70   0.089      .979806    1.329875
        671  |   .9593122   .1012747    -0.39   0.694     .7800071    1.179835
        672  |   1.729997    .562754     1.69   0.092     .9144428    3.272912
        673  |          1  (omitted)
        674  |   .7301038   .1748181    -1.31   0.189     .4566363    1.167344
        675  |   .6384489   .1644231    -1.74   0.081     .3854001    1.057646
        676  |    .694713   .1682663    -1.50   0.133     .4321516    1.116798
        677  |   .9651731   .2502216    -0.14   0.891      .580672    1.604278
        678  |   .9777464   .3224564    -0.07   0.946     .5122757    1.866159
        679  |   .6925408   .1746115    -1.46   0.145     .4225037    1.135168
        680  |   .8464601   .2184503    -0.65   0.518     .5104258     1.40372
        681  |   .5852771    .141762    -2.21   0.027     .3640735    .9408795
        682  |   .4835249   .1120208    -3.14   0.002     .3070552    .7614147
        683  |   .5325497   .1158611    -2.90   0.004      .347675    .8157309
             |
       _cons |   9.65e-06   6.21e-06   -17.93   0.000     2.73e-06    .0000341
ln(popula~n) |          1  (exposure)
------------------------------------------------------------------------------
Note: _cons estimates baseline incidence rate (conditional on zero random effects).
Note: One or more parameters could not be estimated in 15 bootstrap replicates;
      standard-error estimates include only complete replications.

. estat ic

Akaike's information criterion and Bayesian information criterion

-----------------------------------------------------------------------------
       Model |        Obs  ll(null)  ll(model)      df         AIC        BIC
-------------+---------------------------------------------------------------
           . |      1,120         .  -6590.714      75    13331.43   13708.01
-----------------------------------------------------------------------------
               Note: N=Obs used in calculating BIC; see [R] BIC note.

. 
. xtset PanelID MonthYear, monthly
       panel variable:  PanelID (unbalanced)
        time variable:  MonthYear, 2011m1 to 2016m12, but with gaps
                delta:  1 month

. xtnbreg Ped FergEff24 d.UnempL d.OffRateL d.DepScore d.PctNonWhtL  ///
> i.MonthYear if NoCov < 1 & Ped > 0 & weirdPed < 1, fe irr vce(bootstrap, seed(909) ///
> reps(5000) nodots) exposure(population)
note: 679.MonthYear omitted because of collinearity
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered

Conditional FE negative binomial regression     Number of obs     =      1,120
Group variable: PanelID                         Number of groups  =         19

                                                Obs per group:
                                                              min =         15
                                                              avg =       58.9
                                                              max =         71

                                                Wald chi2(74)     =   53949.90
Log likelihood  = -6590.7145                    Prob > chi2       =     0.0000

                                (Replications based on 19 clusters in PanelID)
------------------------------------------------------------------------------
             |   Observed   Bootstrap                         Normal-based
         Ped |        IRR   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   FergEff24 |   .6925408   .1747193    -1.46   0.145     .4223747    1.135515
             |
      UnempL |
         D1. |   .1852777   .1996609    -1.56   0.118     .0224152    1.531454
             |
    OffRateL |
         D1. |   .8001053   .3825984    -0.47   0.641     .3134118     2.04258
             |
    DepScore |
         D1. |   2.245577   1.210044     1.50   0.133     .7810027    6.456594
             |
  PctNonWhtL |
         D1. |    19645.8   229932.2     0.84   0.398     2.14e-06    1.80e+14
             |
   MonthYear |
        614  |    1.28728   .1020992     3.18   0.001     1.101948    1.503783
        615  |   1.098762   .0620575     1.67   0.095     .9836219     1.22738
        616  |   1.323266   .1359229     2.73   0.006     1.081966     1.61838
        617  |   1.370403   .1930369     2.24   0.025     1.039793    1.806133
        618  |   1.289691   .2072954     1.58   0.113     .9411738    1.767264
        619  |   1.251686   .2055884     1.37   0.172     .9071648    1.727048
        620  |   1.199413   .1550221     1.41   0.159     .9310058    1.545201
        621  |   1.141257   .1525446     0.99   0.323     .8782306    1.483058
        622  |   1.001441   .1265653     0.01   0.991     .7817142     1.28293
        623  |    .947486   .1424762    -0.36   0.720      .705627    1.272244
        624  |   1.153128   .2529695     0.65   0.516     .7501427    1.772603
        625  |   .8617436   .2597183    -0.49   0.622     .4773501    1.555676
        626  |   1.168821   .2216027     0.82   0.411     .8060544    1.694851
        627  |   1.123414   .1819419     0.72   0.472     .8178693    1.543106
        628  |   1.135869   .2606763     0.56   0.579     .7244053    1.781044
        629  |   1.197132   .1967398     1.09   0.274     .8674675    1.652078
        630  |    1.22305   .2460223     1.00   0.317     .8245577    1.814126
        631  |   1.083245   .2259991     0.38   0.702     .7196796    1.630475
        632  |   1.080216   .1787298     0.47   0.641     .7810396    1.493992
        633  |   .9807154   .2540927    -0.08   0.940     .5902092    1.629596
        634  |   .8160502   .2448915    -0.68   0.498     .4531863    1.469458
        635  |   .8439005   .2342421    -0.61   0.541     .4898043    1.453985
        636  |   1.097564   .3015248     0.34   0.735     .6405988    1.880501
        637  |    .743274   .1888467    -1.17   0.243     .4517317    1.222974
        638  |   .9960564    .270703    -0.01   0.988     .5847211    1.696755
        639  |   1.034509   .2253009     0.16   0.876     .6750793    1.585307
        640  |    1.22713   .2661095     0.94   0.345     .8022375    1.877059
        641  |   1.428055   .3804615     1.34   0.181     .8471652    2.407251
        642  |   1.157937   .2641682     0.64   0.520     .7404476     1.81082
        643  |   .9725745   .2539925    -0.11   0.915     .5829449    1.622625
        644  |   .9450707   .2288371    -0.23   0.816     .5879717     1.51905
        645  |   1.018408   .2522548     0.07   0.941     .6267337    1.654856
        646  |   .8006981   .2436475    -0.73   0.465      .441015    1.453731
        647  |   .6673541    .235522    -1.15   0.252     .3341574     1.33279
        648  |    .926058   .3419919    -0.21   0.835     .4490459     1.90979
        649  |   .7120147   .2296564    -1.05   0.292     .3783891    1.339798
        650  |   .7822654   .2329817    -0.82   0.410     .4363562    1.402384
        651  |   .7467399   .2344413    -0.93   0.352     .4035822    1.381678
        652  |   1.014989   .2529302     0.06   0.952     .6227968    1.654157
        653  |   1.078904   .2256707     0.36   0.717     .7160442    1.625645
        654  |   1.433003   .4040583     1.28   0.202      .824588    2.490331
        655  |   1.775677    .300569     3.39   0.001     1.274328    2.474269
        656  |   1.656844   .3261003     2.57   0.010     1.126543    2.436774
        657  |   1.238702   .1913293     1.39   0.166     .9151464    1.676652
        658  |   .9765656   .1487344    -0.16   0.876     .7245367    1.316262
        659  |   .9097318   .1540535    -0.56   0.576     .6527868    1.267814
        660  |   1.525123   .2132351     3.02   0.003     1.159562    2.005929
        661  |   .9062358   .1429545    -0.62   0.533     .6652244    1.234566
        662  |   1.021122   .1672182     0.13   0.898     .7407737    1.407569
        663  |   1.132528   .1336531     1.05   0.292     .8986611    1.427256
        664  |   1.760541   .4756005     2.09   0.036     1.036809    2.989466
        665  |   1.679645   .4641695     1.88   0.061     .9772106    2.887001
        666  |   1.694277    .483132     1.85   0.064     .9688569    2.962845
        667  |   1.452807   .3008604     1.80   0.071     .9681298    2.180131
        668  |   1.075109   .1905659     0.41   0.683     .7595826    1.521705
        669  |   1.186942   .1466955     1.39   0.166      .931598    1.512274
        670  |   1.015105   .1258816     0.12   0.904     .7960763    1.294396
        671  |   .8530911   .1190661    -1.14   0.255     .6489229    1.121496
        672  |   1.538441   .3710982     1.79   0.074     .9588629    2.468341
        673  |   .8892737   .1049582    -0.99   0.320     .7056199    1.120728
        674  |   1.054239   .0995279     0.56   0.576     .8761524    1.268525
        675  |   .9218936   .1108349    -0.68   0.499      .728358    1.166855
        676  |   1.003137   .1337323     0.02   0.981     .7724723    1.302679
        677  |    1.39367   .2655021     1.74   0.081     .9594029    2.024504
        678  |   1.411825   .3996868     1.22   0.223     .8105993    2.458983
        679  |          1  (omitted)
        680  |   .8464602   .2185155    -0.65   0.518     .5103487    1.403932
        681  |   .5852771    .141881    -2.21   0.027     .3639284    .9412547
        682  |   .4835249   .1121146    -3.13   0.002     .3069385    .7617041
        683  |   .5325497   .1159676    -2.89   0.004     .3475388    .8160506
             |
       _cons |   9.65e-06   6.21e-06   -17.94   0.000     2.73e-06    .0000341
ln(popula~n) |          1  (exposure)
------------------------------------------------------------------------------
Note: _cons estimates baseline incidence rate (conditional on zero random effects).
Note: One or more parameters could not be estimated in 7 bootstrap replicates;
      standard-error estimates include only complete replications.

. estat ic

Akaike's information criterion and Bayesian information criterion

-----------------------------------------------------------------------------
       Model |        Obs  ll(null)  ll(model)      df         AIC        BIC
-------------+---------------------------------------------------------------
           . |      1,120         .  -6590.714      75    13331.43   13708.01
-----------------------------------------------------------------------------
               Note: N=Obs used in calculating BIC; see [R] BIC note.

. 
. xtset PanelID MonthYear, monthly
       panel variable:  PanelID (unbalanced)
        time variable:  MonthYear, 2011m1 to 2016m12, but with gaps
                delta:  1 month

. xtnbreg Ped FergEff d.UnempL d.OffRateL d.DepScore d.PctNonWhtL  ///
> i.MonthYear if NoCov < 1 & Ped > 0 & weirdPed < 1, fe irr vce(bootstrap, seed(909) ///
> reps(5000) nodots) exposure(population)
note: 683.MonthYear omitted because of collinearity
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered

Conditional FE negative binomial regression     Number of obs     =      1,120
Group variable: PanelID                         Number of groups  =         19

                                                Obs per group:
                                                              min =         15
                                                              avg =       58.9
                                                              max =         71

                                                Wald chi2(74)     =   54003.78
Log likelihood  = -6590.7145                    Prob > chi2       =     0.0000

                                (Replications based on 19 clusters in PanelID)
------------------------------------------------------------------------------
             |   Observed   Bootstrap                         Normal-based
         Ped |        IRR   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     FergEff |   .5325497   .1160229    -2.89   0.004      .347468    .8162167
             |
      UnempL |
         D1. |   .1852778   .1997257    -1.56   0.118     .0223998    1.532504
             |
    OffRateL |
         D1. |   .8001053   .3859279    -0.46   0.644      .310866    2.059307
             |
    DepScore |
         D1. |   2.245577   1.211902     1.50   0.134     .7797372    6.467073
             |
  PctNonWhtL |
         D1. |   19645.83     230020     0.84   0.398     2.12e-06    1.82e+14
             |
   MonthYear |
        614  |    1.28728   .1020482     3.19   0.001     1.102033    1.503666
        615  |   1.098762   .0619597     1.67   0.095     .9837934    1.227166
        616  |   1.323266    .135972     2.73   0.006     1.081887    1.618498
        617  |   1.370403   .1933158     2.23   0.025     1.039379    1.806854
        618  |   1.289691   .2074995     1.58   0.114     .9408819    1.767813
        619  |   1.251686   .2057827     1.37   0.172     .9068887    1.727574
        620  |   1.199413   .1551126     1.41   0.160     .9308681     1.54543
        621  |   1.141257    .152632     0.99   0.323     .8780987     1.48328
        622  |   1.001441   .1266353     0.01   0.991      .781607    1.283106
        623  |    .947486   .1425466    -0.36   0.720     .7055242    1.272429
        624  |   1.153128   .2532209     0.65   0.516     .7498222     1.77336
        625  |   .8617436   .2596744    -0.49   0.621     .4773978    1.555521
        626  |   1.168821   .2215919     0.82   0.411     .8060691    1.694821
        627  |   1.123414   .1819419     0.72   0.472     .8178693    1.543106
        628  |   1.135869   .2606591     0.56   0.579     .7244268    1.780992
        629  |   1.197132   .1966995     1.10   0.273     .8675247    1.651969
        630  |    1.22305   .2460792     1.00   0.317     .8244825    1.814291
        631  |   1.083245   .2259258     0.38   0.701     .7197751    1.630259
        632  |   1.080216   .1787695     0.47   0.641     .7809834      1.4941
        633  |   .9807154   .2540335    -0.08   0.940      .590279    1.629404
        634  |   .8160502   .2448257    -0.68   0.498     .4532578    1.469226
        635  |   .8439004   .2341744    -0.61   0.541     .4898812    1.453756
        636  |   1.097564   .3017219     0.34   0.735     .6403733    1.881163
        637  |    .743274   .1887539    -1.17   0.243     .4518423    1.222675
        638  |   .9960564   .2706316    -0.01   0.988     .5848033    1.696516
        639  |   1.034509   .2253197     0.16   0.876     .6750554    1.585363
        640  |    1.22713   .2663599     0.94   0.346     .8019167     1.87781
        641  |   1.428054   .3808115     1.34   0.181     .8467584    2.408408
        642  |   1.157937   .2643353     0.64   0.521     .7402382    1.811333
        643  |   .9725745   .2539346    -0.11   0.915     .5830129    1.622436
        644  |   .9450706   .2287671    -0.23   0.815      .588057     1.51883
        645  |   1.018408   .2521197     0.07   0.941     .6268967    1.654426
        646  |   .8006981   .2435506    -0.73   0.465     .4411197    1.453387
        647  |   .6673541   .2354858    -1.15   0.252     .3341929    1.332648
        648  |    .926058   .3420357    -0.21   0.835     .4490042    1.909967
        649  |   .7120147   .2296549    -1.05   0.292     .3783907    1.339792
        650  |   .7822654   .2329728    -0.82   0.410      .436366    1.402353
        651  |   .7467399   .2343624    -0.93   0.352     .4036657    1.381392
        652  |   1.014989   .2529332     0.06   0.952     .6227933    1.654166
        653  |   1.078904   .2258038     0.36   0.717      .715871    1.626038
        654  |   1.433003   .4044749     1.27   0.202     .8241182     2.49175
        655  |   2.309135   .3508612     5.51   0.000     1.714405    3.110176
        656  |   2.154601   .3921125     4.22   0.000     1.508196     3.07805
        657  |   1.610838    .243534     3.15   0.002     1.197742    2.166409
        658  |    1.26995    .188874     1.61   0.108     .9488361    1.699738
        659  |   1.183038    .203369     0.98   0.328     .8446437    1.657004
        660  |   1.983308    .273671     4.96   0.000     1.513335    2.599231
        661  |   1.178491    .208793     0.93   0.354     .8327588     1.66776
        662  |   1.327892   .2346522     1.60   0.109     .9391756    1.877495
        663  |   1.472767   .1915924     2.98   0.003     1.141303    1.900496
        664  |    2.28945   .5723744     3.31   0.001     1.402575    3.737111
        665  |   2.184251   .5555964     3.07   0.002     1.326744    3.595988
        666  |   2.203277   .5837072     2.98   0.003      1.31088    3.703184
        667  |   1.889266   .3647527     3.30   0.001     1.294063    2.758234
        668  |   1.398099   .2467514     1.90   0.058     .9892562    1.975909
        669  |   1.543529   .1892416     3.54   0.000     1.213821    1.962794
        670  |   1.320067   .1661135     2.21   0.027     1.031533    1.689308
        671  |   1.109381   .1452843     0.79   0.428     .8582373    1.434015
        672  |   2.000627   .4761007     2.91   0.004     1.254876    3.189565
        673  |   1.156433   .1568338     1.07   0.284     .8865065    1.508549
        674  |   1.370959   .1430374     3.02   0.002     1.117417    1.682029
        675  |   1.198853   .1621011     1.34   0.180     .9197548    1.562644
        676  |   1.304504   .1816527     1.91   0.056     .9929219    1.713861
        677  |   1.812362   .3002936     3.59   0.000     1.309809    2.507738
        678  |   1.835972    .494944     2.25   0.024     1.082425    3.114112
        679  |   1.300425   .0952461     3.59   0.000     1.126526    1.501168
        680  |   1.589448   .2817014     2.61   0.009     1.123016    2.249607
        681  |   1.099009   .0945332     1.10   0.272     .9285039    1.300825
        682  |   .9079431   .1011127    -0.87   0.386     .7299026    1.129412
        683  |          1  (omitted)
             |
       _cons |   9.65e-06   6.21e-06   -17.94   0.000     2.73e-06    .0000341
ln(popula~n) |          1  (exposure)
------------------------------------------------------------------------------
Note: _cons estimates baseline incidence rate (conditional on zero random effects).
Note: One or more parameters could not be estimated in 7 bootstrap replicates;
      standard-error estimates include only complete replications.

. estat ic

Akaike's information criterion and Bayesian information criterion

-----------------------------------------------------------------------------
       Model |        Obs  ll(null)  ll(model)      df         AIC        BIC
-------------+---------------------------------------------------------------
           . |      1,120         .  -6590.714      75    13331.43   13708.01
-----------------------------------------------------------------------------
               Note: N=Obs used in calculating BIC; see [R] BIC note.

. 
. * Total Stops
. 
. xtset PanelID MonthYear, monthly
       panel variable:  PanelID (unbalanced)
        time variable:  MonthYear, 2011m1 to 2016m12, but with gaps
                delta:  1 month

. xtnbreg TStops FergEff1 d.UnempL d.OffRateL d.DepScore d.PctNonWhtL  ///
> i.MonthYear if NoCov < 1 & Ped > 0 & weirdPed < 1, fe irr vce(bootstrap, seed(909) ///
> reps(5000) nodots) exposure(population)
note: 655.MonthYear omitted because of collinearity
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered

Conditional FE negative binomial regression     Number of obs     =      1,120
Group variable: PanelID                         Number of groups  =         19

                                                Obs per group:
                                                              min =         15
                                                              avg =       58.9
                                                              max =         71

                                                Wald chi2(74)     =  197249.26
Log likelihood  = -9251.5071                    Prob > chi2       =     0.0000

                                (Replications based on 19 clusters in PanelID)
------------------------------------------------------------------------------
             |   Observed   Bootstrap                         Normal-based
      TStops |        IRR   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    FergEff1 |   .8296997   .0869636    -1.78   0.075     .6756218    1.018916
             |
      UnempL |
         D1. |   .8374498   .1609979    -0.92   0.356     .5745359    1.220676
             |
    OffRateL |
         D1. |   .6603898   .4230767    -0.65   0.517     .1881398    2.318035
             |
    DepScore |
         D1. |   .9290097    .173165    -0.40   0.693     .6447011    1.338696
             |
  PctNonWhtL |
         D1. |   14.20621   35.96648     1.05   0.295     .0994156    2030.027
             |
   MonthYear |
        614  |   1.146578   .0736664     2.13   0.033     1.010915    1.300446
        615  |   1.006618   .0526468     0.13   0.900     .9085442    1.115277
        616  |   1.049894   .0668776     0.76   0.445     .9266684    1.189506
        617  |   1.054525   .0746632     0.75   0.453     .9178877    1.211502
        618  |   1.034053   .0915931     0.38   0.705     .8692525    1.230097
        619  |   1.055636   .0932593     0.61   0.540     .8878007      1.2552
        620  |   .9736107   .0849127    -0.31   0.759     .8206321    1.155107
        621  |   .9153176   .0755133    -1.07   0.283     .7786604    1.075959
        622  |   .8882343   .0610784    -1.72   0.085     .7762393    1.016388
        623  |   .8571445   .0625906    -2.11   0.035     .7428437    .9890327
        624  |   .9934037    .115891    -0.06   0.955     .7903585    1.248612
        625  |   .9549356   .0857963    -0.51   0.608     .8007516    1.138808
        626  |   .9743966   .1114398    -0.23   0.821     .7787276    1.219231
        627  |   .8627593   .0860416    -1.48   0.139      .709579    1.049007
        628  |   .9477922   .1022978    -0.50   0.619     .7670799    1.171077
        629  |   .8835461   .0708182    -1.54   0.122     .7550983    1.033844
        630  |   .8998573   .0986887    -0.96   0.336     .7258069    1.115645
        631  |   .9064308   .1079698    -0.82   0.410     .7177009     1.14479
        632  |   .8289903   .0951107    -1.63   0.102     .6620494    1.038027
        633  |   .8599368   .0917605    -1.41   0.157     .6976508    1.059973
        634  |   .8145081   .1044729    -1.60   0.110     .6334554    1.047309
        635  |   .7690913   .0987119    -2.05   0.041     .5980358    .9890735
        636  |   .9144324   .1130418    -0.72   0.469     .7176727    1.165137
        637  |   .7717638   .0767636    -2.60   0.009     .6350669    .9378844
        638  |    .960381    .115118    -0.34   0.736     .7592986    1.214715
        639  |   .8215481   .1079568    -1.50   0.135     .6350085    1.062886
        640  |   .8940646   .1084709    -0.92   0.356     .7048526    1.134069
        641  |   .7996118   .0856499    -2.09   0.037     .6481915    .9864046
        642  |    .799416   .0980032    -1.83   0.068     .6286676     1.01654
        643  |   .8637987   .1066428    -1.19   0.236     .6781488    1.100272
        644  |    .806277   .1079201    -1.61   0.108     .6202276    1.048136
        645  |   .8503717   .1120721    -1.23   0.219     .6567912    1.101008
        646  |   .8065808   .1072006    -1.62   0.106     .6216083    1.046596
        647  |   .7392931   .1048521    -2.13   0.033     .5598774    .9762036
        648  |   .8462202   .1315254    -1.07   0.283     .6239988     1.14758
        649  |   .7927685   .1111364    -1.66   0.098     .6023077    1.043456
        650  |     .81992   .1010494    -1.61   0.107     .6439717    1.043941
        651  |   .8024521   .0993386    -1.78   0.075     .6295724    1.022804
        652  |   .8520218     .09255    -1.47   0.140     .6886361    1.054172
        653  |   .7713288   .0788963    -2.54   0.011     .6312093    .9425528
        654  |   .8497399   .0979943    -1.41   0.158     .6778337    1.065243
        655  |          1  (omitted)
        656  |   .7866807   .0878381    -2.15   0.032      .632057    .9791308
        657  |   .7675624   .0802814    -2.53   0.011     .6252939    .9422001
        658  |   .6785947   .0623576    -4.22   0.000     .5667501    .8125112
        659  |   .6028078   .0545234    -5.60   0.000     .5048804    .7197293
        660  |   .7071459   .0698738    -3.51   0.000     .5826408    .8582566
        661  |   .6710794    .064935    -4.12   0.000     .5551495    .8112185
        662  |   .7113289   .0687507    -3.52   0.000     .5885739    .8596862
        663  |   .6886734   .0650219    -3.95   0.000     .5723294    .8286679
        664  |   .7286384   .0651334    -3.54   0.000     .6115368    .8681634
        665  |   .7015769    .065095    -3.82   0.000     .5849214    .8414979
        666  |   .6784725   .0665385    -3.96   0.000     .5598272    .8222625
        667  |   .7179154    .062487    -3.81   0.000       .60532    .8514545
        668  |   .7031422   .0628676    -3.94   0.000     .5901164     .837816
        669  |   .7329557   .0686868    -3.32   0.001      .609972    .8807356
        670  |   .6626042   .0613101    -4.45   0.000     .5527049    .7943557
        671  |   .5933471   .0557251    -5.56   0.000     .4935907    .7132645
        672  |   .7399525   .0819396    -2.72   0.007     .5955866    .9193116
        673  |   .7293008   .0860119    -2.68   0.007     .5787861    .9189572
        674  |    .766297   .0919513    -2.22   0.027     .6057002    .9694748
        675  |   .6770985   .0875533    -3.02   0.003     .5255159    .8724044
        676  |   .7216439   .0868862    -2.71   0.007     .5699515     .913709
        677  |   .7173166   .1064295    -2.24   0.025     .5363109    .9594121
        678  |   .6739967   .1150403    -2.31   0.021     .4823602    .9417683
        679  |   .7443933   .1135415    -1.94   0.053     .5520388    1.003772
        680  |   .7172638   .1129556    -2.11   0.035     .5267817    .9766235
        681  |   .6720852   .1114104    -2.40   0.017     .4856486    .9300932
        682  |    .601116   .0973929    -3.14   0.002     .4375689    .8257908
        683  |   .6192307   .1065289    -2.79   0.005     .4419943    .8675375
             |
       _cons |   .0000398   .0000145   -27.87   0.000     .0000195    .0000812
ln(popula~n) |          1  (exposure)
------------------------------------------------------------------------------
Note: _cons estimates baseline incidence rate (conditional on zero random effects).
Note: One or more parameters could not be estimated in 19 bootstrap replicates;
      standard-error estimates include only complete replications.

. estat ic

Akaike's information criterion and Bayesian information criterion

-----------------------------------------------------------------------------
       Model |        Obs  ll(null)  ll(model)      df         AIC        BIC
-------------+---------------------------------------------------------------
           . |      1,120         .  -9251.507      75    18653.01    19029.6
-----------------------------------------------------------------------------
               Note: N=Obs used in calculating BIC; see [R] BIC note.

. 
. xtset PanelID MonthYear, monthly
       panel variable:  PanelID (unbalanced)
        time variable:  MonthYear, 2011m1 to 2016m12, but with gaps
                delta:  1 month

. xtnbreg TStops FergEff6 d.UnempL d.OffRateL d.DepScore d.PctNonWhtL  ///
> i.MonthYear if NoCov < 1 & Ped > 0 & weirdPed < 1, fe irr vce(bootstrap, seed(909) ///
> reps(5000) nodots) exposure(population)
note: 661.MonthYear omitted because of collinearity
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered

Conditional FE negative binomial regression     Number of obs     =      1,120
Group variable: PanelID                         Number of groups  =         19

                                                Obs per group:
                                                              min =         15
                                                              avg =       58.9
                                                              max =         71

                                                Wald chi2(74)     =  197492.31
Log likelihood  = -9251.5071                    Prob > chi2       =     0.0000

                                (Replications based on 19 clusters in PanelID)
------------------------------------------------------------------------------
             |   Observed   Bootstrap                         Normal-based
      TStops |        IRR   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    FergEff6 |   .6710794   .0650651    -4.11   0.000     .5549386    .8115268
             |
      UnempL |
         D1. |   .8374498   .1609671    -0.92   0.356     .5745773    1.220588
             |
    OffRateL |
         D1. |   .6603898   .4229267    -0.65   0.517     .1882236    2.317003
             |
    DepScore |
         D1. |   .9290095   .1731792    -0.40   0.693     .6446817    1.338736
             |
  PctNonWhtL |
         D1. |   14.20628   35.93468     1.05   0.294     .0998557    2021.101
             |
   MonthYear |
        614  |   1.146578   .0736858     2.13   0.033     1.010882    1.300489
        615  |   1.006618   .0526511     0.13   0.900     .9085366    1.115287
        616  |   1.049894   .0668597     0.76   0.445     .9266994    1.189466
        617  |   1.054525   .0746568     0.75   0.453     .9178986    1.211488
        618  |   1.034053   .0916272     0.38   0.706     .8691962    1.230177
        619  |   1.055636   .0933387     0.61   0.540     .8876699    1.255385
        620  |   .9736107   .0849506    -0.31   0.759     .8205694    1.155195
        621  |   .9153176   .0755556    -1.07   0.284     .7785898    1.076056
        622  |   .8882343   .0611289    -1.72   0.085     .7761529    1.016501
        623  |   .8571445     .06263    -2.11   0.035     .7427767    .9891219
        624  |   .9934037   .1158901    -0.06   0.955       .79036    1.248609
        625  |   .9549356   .0858835    -0.51   0.608     .8006083    1.139012
        626  |   .9743966   .1115527    -0.23   0.821     .7785507    1.219508
        627  |   .8627593   .0861431    -1.48   0.139     .7094153     1.04925
        628  |   .9477922   .1023739    -0.50   0.620     .7669593    1.171262
        629  |    .883546   .0708918    -1.54   0.123     .7549749    1.034013
        630  |   .8998573   .0988008    -0.96   0.337     .7256296    1.115918
        631  |   .9064308   .1080714    -0.82   0.410     .7175433    1.145041
        632  |   .8289903   .0952159    -1.63   0.102     .6618848    1.038285
        633  |   .8599368   .0918381    -1.41   0.158     .6975275    1.060161
        634  |   .8145081   .1045733    -1.60   0.110     .6333022    1.047562
        635  |   .7690913   .0988027    -2.04   0.041     .5978975    .9893023
        636  |   .9144324   .1131082    -0.72   0.470     .7175705    1.165302
        637  |   .7717638   .0768187    -2.60   0.009      .634978    .9380157
        638  |    .960381   .1152137    -0.34   0.736     .7591503    1.214953
        639  |   .8215481   .1080512    -1.49   0.135     .6348656    1.063125
        640  |   .8940646   .1085816    -0.92   0.357     .7046815    1.134344
        641  |   .7996118   .0857499    -2.09   0.037     .6480326    .9866465
        642  |    .799416   .0981224    -1.82   0.068      .628484    1.016837
        643  |   .8637987   .1067732    -1.18   0.236     .6779481    1.100598
        644  |    .806277   .1080444    -1.61   0.108     .6200402    1.048452
        645  |   .8503717   .1121644    -1.23   0.219     .6566515    1.101242
        646  |   .8065808   .1073018    -1.62   0.106     .6214556    1.046853
        647  |   .7392931   .1049335    -2.13   0.033     .5597565    .9764145
        648  |   .8462201   .1316293    -1.07   0.283     .6238486    1.147856
        649  |   .7927685   .1112089    -1.66   0.098     .6021997    1.043644
        650  |     .81992     .10113    -1.61   0.107     .6438478    1.044142
        651  |   .8024521   .0994377    -1.78   0.076       .62942    1.023052
        652  |   .8520218   .0926502    -1.47   0.141     .6884774    1.054415
        653  |   .7713288   .0789955    -2.54   0.011     .6310501    .9427904
        654  |   .8497399   .0981181    -1.41   0.159     .6776402    1.065548
        655  |   1.236366   .0560224     4.68   0.000     1.131299    1.351191
        656  |   1.172262   .0516501     3.61   0.000     1.075277    1.277994
        657  |   1.143773   .0399182     3.85   0.000      1.06815    1.224749
        658  |   1.011199   .0338002     0.33   0.739     .9470751    1.079664
        659  |    .898266   .0342562    -2.81   0.005      .833573    .9679797
        660  |   1.053744   .0492791     1.12   0.263      .961453    1.154894
        661  |          1  (omitted)
        662  |   .7113289   .0688786    -3.52   0.000     .5883664    .8599893
        663  |   .6886734   .0651403    -3.94   0.000     .5721366    .8289471
        664  |   .7286384   .0652352    -3.54   0.000     .6113694    .8684012
        665  |   .7015769   .0651766    -3.82   0.000     .5847881    .8416898
        666  |   .6784725   .0666169    -3.95   0.000     .5597004    .8224488
        667  |   .7179154   .0625697    -3.80   0.000     .6051835    .8516466
        668  |   .7031422   .0629492    -3.93   0.000     .5899821    .8380066
        669  |   .7329557   .0688063    -3.31   0.001     .6097771    .8810171
        670  |   .6626042   .0614253    -4.44   0.000     .5525167    .7946263
        671  |   .5933471   .0558043    -5.55   0.000     .4934615    .7134513
        672  |   .7399525   .0820263    -2.72   0.007     .5954498    .9195228
        673  |   .7293008   .0860901    -2.67   0.007     .5786645    .9191503
        674  |    .766297   .0920397    -2.22   0.027     .6055634    .9696939
        675  |   .6770985   .0876233    -3.01   0.003     .5254095    .8725811
        676  |   .7216439   .0869452    -2.71   0.007     .5698603    .9138554
        677  |   .7173166   .1064357    -2.24   0.025     .5363019    .9594281
        678  |   .6739967   .1150537    -2.31   0.021     .4823415    .9418049
        679  |   .7443933    .113641    -1.93   0.053     .5518941    1.004036
        680  |   .7172638   .1130222    -2.11   0.035     .5266857    .9768014
        681  |   .6720852   .1114344    -2.40   0.017     .4856146    .9301584
        682  |    .601116   .0973968    -3.14   0.002     .4375634    .8258012
        683  |   .6192307   .1065231    -2.79   0.005     .4420024    .8675217
             |
       _cons |   .0000398   .0000145   -27.89   0.000     .0000195    .0000812
ln(popula~n) |          1  (exposure)
------------------------------------------------------------------------------
Note: _cons estimates baseline incidence rate (conditional on zero random effects).
Note: One or more parameters could not be estimated in 15 bootstrap replicates;
      standard-error estimates include only complete replications.

. estat ic

Akaike's information criterion and Bayesian information criterion

-----------------------------------------------------------------------------
       Model |        Obs  ll(null)  ll(model)      df         AIC        BIC
-------------+---------------------------------------------------------------
           . |      1,120         .  -9251.507      75    18653.01    19029.6
-----------------------------------------------------------------------------
               Note: N=Obs used in calculating BIC; see [R] BIC note.

. 
. xtset PanelID MonthYear, monthly
       panel variable:  PanelID (unbalanced)
        time variable:  MonthYear, 2011m1 to 2016m12, but with gaps
                delta:  1 month

. xtnbreg TStops FergEff12 d.UnempL d.OffRateL d.DepScore d.PctNonWhtL  ///
> i.MonthYear if NoCov < 1 & Ped > 0 & weirdPed < 1, fe irr vce(bootstrap, seed(909) ///
> reps(5000) nodots) exposure(population)
note: 667.MonthYear omitted because of collinearity
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered

Conditional FE negative binomial regression     Number of obs     =      1,120
Group variable: PanelID                         Number of groups  =         19

                                                Obs per group:
                                                              min =         15
                                                              avg =       58.9
                                                              max =         71

                                                Wald chi2(74)     =  197387.97
Log likelihood  = -9251.5071                    Prob > chi2       =     0.0000

                                (Replications based on 19 clusters in PanelID)
------------------------------------------------------------------------------
             |   Observed   Bootstrap                         Normal-based
      TStops |        IRR   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   FergEff12 |   .7179154   .0625521    -3.80   0.000     .6052126    .8516057
             |
      UnempL |
         D1. |   .8374498    .161032    -0.92   0.356       .57449    1.220773
             |
    OffRateL |
         D1. |   .6603898   .4228276    -0.65   0.517      .188279    2.316322
             |
    DepScore |
         D1. |   .9290096   .1731357    -0.40   0.693      .644741    1.338613
             |
  PctNonWhtL |
         D1. |   14.20623   35.93714     1.05   0.294     .0998196    2021.817
             |
   MonthYear |
        614  |   1.146578   .0736912     2.13   0.033     1.010873    1.300502
        615  |   1.006618   .0526444     0.13   0.900     .9085485    1.115272
        616  |   1.049894     .06685     0.76   0.444     .9267162    1.189444
        617  |   1.054525   .0746606     0.75   0.453     .9178922    1.211496
        618  |   1.034053   .0916198     0.38   0.705     .8692084    1.230159
        619  |   1.055636   .0933168     0.61   0.540      .887706    1.255334
        620  |   .9736107   .0849386    -0.31   0.759     .8205893    1.155167
        621  |   .9153176   .0755416    -1.07   0.284     .7786131    1.076024
        622  |   .8882343   .0611108    -1.72   0.085     .7761838     1.01646
        623  |   .8571445   .0626068    -2.11   0.035     .7428162    .9890693
        624  |   .9934037   .1158802    -0.06   0.955     .7903754    1.248585
        625  |   .9549356   .0858607    -0.51   0.608     .8006457    1.138958
        626  |   .9743966   .1115215    -0.23   0.821     .7785995    1.219431
        627  |   .8627593   .0861136    -1.48   0.139     .7094628    1.049179
        628  |   .9477922    .102328    -0.50   0.619      .767032    1.171151
        629  |    .883546    .070863    -1.54   0.123     .7550232    1.033946
        630  |   .8998573   .0987646    -0.96   0.336     .7256869     1.11583
        631  |   .9064308   .1080223    -0.82   0.410     .7176195     1.14492
        632  |   .8289903   .0951734    -1.63   0.102     .6619512     1.03818
        633  |   .8599368    .091798    -1.41   0.157     .6975912    1.060064
        634  |   .8145081   .1045226    -1.60   0.110     .6333797    1.047434
        635  |   .7690913   .0987522    -2.04   0.041     .5979744    .9891751
        636  |   .9144324   .1130808    -0.72   0.469     .7176126    1.165234
        637  |   .7717638   .0768078    -2.60   0.009     .6349956    .9379896
        638  |    .960381   .1151942    -0.34   0.736     .7591804    1.214904
        639  |   .8215481   .1080255    -1.49   0.135     .6349045     1.06306
        640  |   .8940646   .1085371    -0.92   0.356     .7047504    1.134234
        641  |   .7996118   .0857239    -2.09   0.037     .6480739    .9865836
        642  |    .799416   .0980739    -1.82   0.068     .6285586    1.016717
        643  |   .8637987   .1067218    -1.19   0.236     .6780272     1.10047
        644  |    .806277   .1079905    -1.61   0.108     .6201214    1.048315
        645  |   .8503717   .1121093    -1.23   0.219     .6567349    1.101102
        646  |   .8065808   .1072565    -1.62   0.106     .6215239    1.046738
        647  |   .7392931   .1048835    -2.13   0.033     .5598307     .976285
        648  |   .8462201   .1315675    -1.07   0.283     .6239379    1.147692
        649  |   .7927685   .1111767    -1.66   0.098     .6022477     1.04356
        650  |     .81992   .1010927    -1.61   0.107     .6439052    1.044049
        651  |   .8024521   .0994022    -1.78   0.076     .6294746    1.022963
        652  |   .8520218   .0926161    -1.47   0.141     .6885314    1.054333
        653  |   .7713288   .0789728    -2.54   0.011     .6310865    .9427362
        654  |   .8497399   .0980768    -1.41   0.158     .6777047    1.065446
        655  |   1.155707   .0808874     2.07   0.039     1.007564    1.325632
        656  |   1.095785   .0865215     1.16   0.247     .9386759    1.279189
        657  |   1.069154   .0665996     1.07   0.283     .9462754     1.20799
        658  |   .9452294   .0402056    -1.32   0.185     .8696233    1.027409
        659  |   .8396641   .0257243    -5.70   0.000     .7907294    .8916273
        660  |   .9849989   .0641447    -0.23   0.816     .8669702    1.119096
        661  |   .9347612   .0457464    -1.38   0.168     .8492657    1.028863
        662  |   .9908256   .0414006    -0.22   0.825     .9129157    1.075384
        663  |   .9592682    .037122    -1.07   0.283     .8892012    1.034856
        664  |   1.014936   .0335994     0.45   0.654     .9511736    1.082973
        665  |   .9772417   .0310293    -0.73   0.468     .9182791     1.03999
        666  |   .9450591   .0373805    -1.43   0.153     .8745625    1.021238
        667  |          1  (omitted)
        668  |   .7031422   .0629349    -3.93   0.000     .5900056    .8379732
        669  |   .7329557   .0687892    -3.31   0.001     .6098049    .8809769
        670  |   .6626042   .0614112    -4.44   0.000     .5525397    .7945933
        671  |   .5933471   .0557908    -5.55   0.000     .4934835    .7134194
        672  |   .7399525   .0820278    -2.72   0.007     .5954475    .9195264
        673  |   .7293008   .0860809    -2.67   0.007     .5786788    .9191277
        674  |    .766297   .0920316    -2.22   0.027     .6055759    .9696738
        675  |   .6770985   .0876152    -3.01   0.003     .5254218    .8725607
        676  |   .7216439   .0869326    -2.71   0.007     .5698797    .9138241
        677  |   .7173166   .1064413    -2.24   0.025     .5362936     .959443
        678  |   .6739967   .1150517    -2.31   0.021     .4823443    .9417995
        679  |   .7443933   .1136218    -1.93   0.053      .551922    1.003985
        680  |   .7172638   .1129963    -2.11   0.035      .526723    .9767322
        681  |   .6720852   .1114173    -2.40   0.017     .4856388     .930112
        682  |    .601116   .0973728    -3.14   0.002     .4375976    .8257367
        683  |   .6192307   .1065075    -2.79   0.005     .4420242     .867479
             |
       _cons |   .0000398   .0000145   -27.88   0.000     .0000195    .0000812
ln(popula~n) |          1  (exposure)
------------------------------------------------------------------------------
Note: _cons estimates baseline incidence rate (conditional on zero random effects).
Note: One or more parameters could not be estimated in 12 bootstrap replicates;
      standard-error estimates include only complete replications.

. estat ic

Akaike's information criterion and Bayesian information criterion

-----------------------------------------------------------------------------
       Model |        Obs  ll(null)  ll(model)      df         AIC        BIC
-------------+---------------------------------------------------------------
           . |      1,120         .  -9251.507      75    18653.01    19029.6
-----------------------------------------------------------------------------
               Note: N=Obs used in calculating BIC; see [R] BIC note.

. 
. xtset PanelID MonthYear, monthly
       panel variable:  PanelID (unbalanced)
        time variable:  MonthYear, 2011m1 to 2016m12, but with gaps
                delta:  1 month

. xtnbreg TStops FergEff18 d.UnempL d.OffRateL d.DepScore d.PctNonWhtL  ///
> i.MonthYear if NoCov < 1 & Ped > 0 & weirdPed < 1, fe irr vce(bootstrap, seed(909) ///
> reps(5000) nodots) exposure(population)
note: 673.MonthYear omitted because of collinearity
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered

Conditional FE negative binomial regression     Number of obs     =      1,120
Group variable: PanelID                         Number of groups  =         19

                                                Obs per group:
                                                              min =         15
                                                              avg =       58.9
                                                              max =         71

                                                Wald chi2(74)     =  197544.44
Log likelihood  = -9251.5071                    Prob > chi2       =     0.0000

                                (Replications based on 19 clusters in PanelID)
------------------------------------------------------------------------------
             |   Observed   Bootstrap                         Normal-based
      TStops |        IRR   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   FergEff18 |   .7293008   .0860346    -2.68   0.007     .5787508    .9190133
             |
      UnempL |
         D1. |   .8374498   .1609856    -0.92   0.356     .5745525    1.220641
             |
    OffRateL |
         D1. |   .6603895   .4226804    -0.65   0.517     .1883611     2.31531
             |
    DepScore |
         D1. |   .9290097   .1731697    -0.40   0.693     .6446949    1.338709
             |
  PctNonWhtL |
         D1. |   14.20609   35.94702     1.05   0.294     .0996777    2024.655
             |
   MonthYear |
        614  |   1.146578    .073662     2.13   0.033     1.010923    1.300436
        615  |   1.006618   .0526364     0.13   0.900     .9085625    1.115255
        616  |   1.049894   .0668417     0.76   0.444     .9267306    1.189426
        617  |   1.054525   .0746308     0.75   0.453      .917943    1.211429
        618  |   1.034053   .0915801     0.38   0.705     .8692739    1.230067
        619  |   1.055636   .0932847     0.61   0.540     .8877589    1.255259
        620  |   .9736107   .0849092    -0.31   0.759     .8206378    1.155099
        621  |   .9153176   .0755164    -1.07   0.283     .7786552    1.075966
        622  |   .8882343   .0610887    -1.72   0.085     .7762217    1.016411
        623  |   .8571445   .0625974    -2.11   0.035      .742832    .9890482
        624  |   .9934037   .1158378    -0.06   0.955     .7904416    1.248481
        625  |   .9549356   .0857998    -0.51   0.608     .8007459    1.138816
        626  |   .9743966    .111445    -0.23   0.821     .7787194    1.219244
        627  |   .8627593   .0860462    -1.48   0.139     .7095715    1.049019
        628  |   .9477922   .1022509    -0.50   0.619     .7671543    1.170964
        629  |    .883546   .0708067    -1.54   0.122     .7551176    1.033817
        630  |   .8998573    .098683    -0.96   0.336      .725816    1.115631
        631  |   .9064308   .1079388    -0.82   0.409      .717749    1.144713
        632  |   .8289903   .0950919    -1.63   0.102     .6620788     1.03798
        633  |   .8599368    .091727    -1.41   0.157     .6977042    1.059892
        634  |   .8145081   .1044339    -1.60   0.110     .6335148    1.047211
        635  |   .7690913   .0986727    -2.05   0.041     .5980956    .9889747
        636  |   .9144324   .1130101    -0.72   0.469     .7177214    1.165057
        637  |   .7717638   .0767564    -2.60   0.009     .6350785    .9378673
        638  |   .9603809   .1151211    -0.34   0.736     .7592937    1.214723
        639  |   .8215481   .1079541    -1.50   0.135     .6350127    1.062879
        640  |   .8940646   .1084478    -0.92   0.356     .7048882    1.134012
        641  |   .7996118   .0856481    -2.09   0.037     .6481944    .9864002
        642  |    .799416   .0979742    -1.83   0.068     .6287124    1.016468
        643  |   .8637987   .1066169    -1.19   0.236     .6781886    1.100208
        644  |    .806277   .1078866    -1.61   0.108     .6202781     1.04805
        645  |   .8503717   .1120219    -1.23   0.219     .6568671     1.10088
        646  |   .8065808   .1071715    -1.62   0.106     .6216523    1.046522
        647  |   .7392931   .1048144    -2.13   0.033     .5599334    .9761061
        648  |   .8462202   .1314643    -1.07   0.282     .6240871    1.147418
        649  |   .7927685   .1111258    -1.66   0.098     .6023235    1.043429
        650  |     .81992   .1010381    -1.61   0.107     .6439892    1.043913
        651  |   .8024521   .0993259    -1.78   0.075     .6295918    1.022773
        652  |   .8520218   .0925347    -1.47   0.140     .6886603    1.054135
        653  |   .7713288   .0788983    -2.54   0.011     .6312059    .9425577
        654  |   .8497399    .097989    -1.41   0.158      .677842     1.06523
        655  |   1.137665   .1328211     1.10   0.269     .9049767    1.430181
        656  |   1.078678   .1186822     0.69   0.491     .8694364    1.338276
        657  |   1.052463   .1174209     0.46   0.647     .8457469    1.309705
        658  |    .930473   .0883218    -0.76   0.448     .7725143     1.12073
        659  |   .8265558   .0749269    -2.10   0.036      .692008    .9872639
        660  |   .9696218   .0937684    -0.32   0.750      .802206    1.171976
        661  |   .9201682   .0892477    -0.86   0.391     .7608668    1.112822
        662  |   .9753574    .082206    -0.30   0.767     .8268409     1.15055
        663  |   .9442926   .0849133    -0.64   0.524     .7917067    1.126287
        664  |   .9990917   .0808137    -0.01   0.991     .8526171     1.17073
        665  |   .9619856   .0786723    -0.47   0.636     .8195138    1.129226
        666  |   .9303054    .079884    -0.84   0.400     .7862018    1.100822
        667  |   .9843886   .0930014    -0.17   0.868     .8179903    1.184636
        668  |   .9641319   .0926341    -0.38   0.704     .7986431    1.163912
        669  |   1.005011   .0879023     0.06   0.954     .8466843    1.192945
        670  |   .9085472   .0751344    -1.16   0.246     .7726013    1.068414
        671  |   .8135834   .0770026    -2.18   0.029     .6758326    .9794112
        672  |   1.014605   .0681893     0.22   0.829     .8893852    1.157456
        673  |          1  (omitted)
        674  |    .766297   .0919814    -2.22   0.027     .6056537    .9695493
        675  |   .6770985   .0875731    -3.01   0.003     .5254858    .8724544
        676  |   .7216438   .0868959    -2.71   0.007     .5699366     .913733
        677  |   .7173166   .1064098    -2.24   0.025     .5363398    .9593603
        678  |   .6739967   .1150477    -2.31   0.021     .4823499    .9417886
        679  |   .7443933    .113582    -1.93   0.053     .5519799     1.00388
        680  |   .7172638   .1129744    -2.11   0.035     .5267546    .9766737
        681  |   .6720852   .1114044    -2.40   0.017     .4856571     .930077
        682  |    .601116   .0973701    -3.14   0.002     .4376015    .8257293
        683  |   .6192307   .1064976    -2.79   0.005     .4420381    .8674517
             |
       _cons |   .0000398   .0000145   -27.88   0.000     .0000195    .0000812
ln(popula~n) |          1  (exposure)
------------------------------------------------------------------------------
Note: _cons estimates baseline incidence rate (conditional on zero random effects).
Note: One or more parameters could not be estimated in 9 bootstrap replicates;
      standard-error estimates include only complete replications.

. estat ic

Akaike's information criterion and Bayesian information criterion

-----------------------------------------------------------------------------
       Model |        Obs  ll(null)  ll(model)      df         AIC        BIC
-------------+---------------------------------------------------------------
           . |      1,120         .  -9251.507      75    18653.01    19029.6
-----------------------------------------------------------------------------
               Note: N=Obs used in calculating BIC; see [R] BIC note.

. 
. xtset PanelID MonthYear, monthly
       panel variable:  PanelID (unbalanced)
        time variable:  MonthYear, 2011m1 to 2016m12, but with gaps
                delta:  1 month

. xtnbreg TStops FergEff24 d.UnempL d.OffRateL d.DepScore d.PctNonWhtL  ///
> i.MonthYear if NoCov < 1 & Ped > 0 & weirdPed < 1, fe irr vce(bootstrap, seed(909) ///
> reps(5000) nodots) exposure(population)
note: 679.MonthYear omitted because of collinearity
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered

Conditional FE negative binomial regression     Number of obs     =      1,120
Group variable: PanelID                         Number of groups  =         19

                                                Obs per group:
                                                              min =         15
                                                              avg =       58.9
                                                              max =         71

                                                Wald chi2(74)     =  197524.89
Log likelihood  = -9251.5071                    Prob > chi2       =     0.0000

                                (Replications based on 19 clusters in PanelID)
------------------------------------------------------------------------------
             |   Observed   Bootstrap                         Normal-based
      TStops |        IRR   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   FergEff24 |   .7443932   .1135208    -1.94   0.053     .5520688    1.003718
             |
      UnempL |
         D1. |     .83745    .161005    -0.92   0.356     .5745265    1.220697
             |
    OffRateL |
         D1. |   .6603889   .4227903    -0.65   0.517     .1882993    2.316066
             |
    DepScore |
         D1. |   .9290091   .1731881    -0.39   0.693     .6446692    1.338761
             |
  PctNonWhtL |
         D1. |   14.20625    35.9375     1.05   0.294     .0998155    2021.906
             |
   MonthYear |
        614  |   1.146578   .0736329     2.13   0.033     1.010973    1.300372
        615  |   1.006617   .0526169     0.13   0.900      .908597    1.115212
        616  |   1.049894   .0668135     0.77   0.444     .9267794    1.189363
        617  |   1.054525   .0746374     0.75   0.453     .9179317    1.211444
        618  |   1.034053   .0915526     0.38   0.705      .869319    1.230003
        619  |   1.055636   .0932035     0.61   0.540     .8878927     1.25507
        620  |   .9736107   .0848816    -0.31   0.759     .8206834    1.155035
        621  |   .9153176   .0754871    -1.07   0.283     .7787041    1.075898
        622  |   .8882343   .0610297    -1.72   0.085     .7763227    1.016279
        623  |   .8571445   .0625033    -2.11   0.035     .7429919    .9888353
        624  |   .9934037   .1158573    -0.06   0.955     .7904111    1.248529
        625  |   .9549356   .0857529    -0.51   0.608     .8008228    1.138706
        626  |   .9743966   .1113644    -0.23   0.820     .7788456    1.219046
        627  |   .8627593   .0859925    -1.48   0.139     .7096581     1.04889
        628  |   .9477921   .1022438    -0.50   0.619     .7671656    1.170947
        629  |    .883546     .07077    -1.55   0.122      .755179    1.033733
        630  |   .8998572   .0986389    -0.96   0.336     .7258856    1.115524
        631  |   .9064308   .1079179    -0.83   0.409     .7177815    1.144661
        632  |   .8289902    .095069    -1.64   0.102     .6621147    1.037924
        633  |   .8599368   .0917231    -1.41   0.157     .6977104    1.059883
        634  |   .8145081   .1044239    -1.60   0.110     .6335301    1.047185
        635  |   .7690912   .0986522    -2.05   0.041     .5981268     .988923
        636  |   .9144324   .1129745    -0.72   0.469     .7177761    1.164969
        637  |   .7717638   .0767539    -2.61   0.009     .6350825    .9378613
        638  |   .9603809   .1150857    -0.34   0.736     .7593486    1.214635
        639  |   .8215481   .1079232    -1.50   0.135     .6350594      1.0628
        640  |   .8940646   .1084271    -0.92   0.356     .7049203     1.13396
        641  |   .7996118   .0855998    -2.09   0.037     .6482711    .9862834
        642  |    .799416   .0979436    -1.83   0.068     .6287594    1.016392
        643  |   .8637987   .1065914    -1.19   0.235     .6782279    1.100144
        644  |    .806277   .1078642    -1.61   0.107     .6203118    1.047993
        645  |   .8503717   .1119976    -1.23   0.218      .656904    1.100818
        646  |   .8065808    .107125    -1.62   0.106     .6217226    1.046403
        647  |   .7392931    .104785    -2.13   0.033     .5599769    .9760301
        648  |   .8462201   .1314335    -1.08   0.282     .6241315    1.147336
        649  |   .7927684   .1111209    -1.66   0.098     .6023307    1.043417
        650  |     .81992   .1010304    -1.61   0.107      .644001    1.043894
        651  |   .8024521   .0992969    -1.78   0.075     .6296364      1.0227
        652  |   .8520218   .0925051    -1.48   0.140     .6887072    1.054063
        653  |   .7713287   .0788495    -2.54   0.011     .6312843    .9424406
        654  |   .8497399   .0979499    -1.41   0.158     .6779031    1.065134
        655  |   1.114599   .1563225     0.77   0.439     .8467154    1.467235
        656  |   1.056808   .1373617     0.43   0.671     .8191409    1.363432
        657  |   1.031125   .1437399     0.22   0.826     .7846082    1.355095
        658  |   .9116078   .1183974    -0.71   0.476     .7067342    1.175872
        659  |   .8097975   .1042971    -1.64   0.101     .6291392    1.042332
        660  |   .9499626   .1227794    -0.40   0.691     .7373806    1.223831
        661  |   .9015119   .1134629    -0.82   0.410     .7044344    1.153725
        662  |   .9555822   .1140293    -0.38   0.703     .7563006    1.207373
        663  |   .9251473   .1180995    -0.61   0.542     .7203621    1.188149
        664  |   .9788352   .1202148    -0.17   0.862     .7694317    1.245229
        665  |   .9424815    .117342    -0.48   0.634     .7384065    1.202957
        666  |   .9114436   .1180034    -0.72   0.474     .7071733    1.174718
        667  |   .9644303   .1302513    -0.27   0.789     .7401362    1.256695
        668  |   .9445843   .1269141    -0.42   0.671     .7258945    1.229159
        669  |   .9846351   .1240751    -0.12   0.902     .7691558    1.260481
        670  |   .8901265   .1078898    -0.96   0.337     .7019075    1.128817
        671  |   .7970882   .1085406    -1.67   0.096     .6103754    1.040916
        672  |   .9940344   .0878777    -0.07   0.946     .8358934    1.182094
        673  |   .9797252   .0521854    -0.38   0.701     .8826017    1.087536
        674  |   1.029425   .0622468     0.48   0.632     .9143756     1.15895
        675  |   .9095978   .0642116    -1.34   0.180     .7920639    1.044573
        676  |    .969439   .0690547    -0.44   0.663     .8431174    1.114687
        677  |   .9636259   .0775449    -0.46   0.645     .8230202    1.128253
        678  |    .905431   .0434597    -2.07   0.038     .8241355    .9947458
        679  |          1  (omitted)
        680  |   .7172638     .11293    -2.11   0.035     .5268184    .9765553
        681  |   .6720852   .1113836    -2.40   0.016     .4856866    .9300205
        682  |   .6011159   .0973592    -3.14   0.002     .4376169    .8257002
        683  |   .6192307   .1064843    -2.79   0.005     .4420567     .867415
             |
       _cons |   .0000398   .0000145   -27.88   0.000     .0000195    .0000812
ln(popula~n) |          1  (exposure)
------------------------------------------------------------------------------
Note: _cons estimates baseline incidence rate (conditional on zero random effects).
Note: One or more parameters could not be estimated in 12 bootstrap replicates;
      standard-error estimates include only complete replications.

. estat ic

Akaike's information criterion and Bayesian information criterion

-----------------------------------------------------------------------------
       Model |        Obs  ll(null)  ll(model)      df         AIC        BIC
-------------+---------------------------------------------------------------
           . |      1,120         .  -9251.507      75    18653.01    19029.6
-----------------------------------------------------------------------------
               Note: N=Obs used in calculating BIC; see [R] BIC note.

. 
. xtset PanelID MonthYear, monthly
       panel variable:  PanelID (unbalanced)
        time variable:  MonthYear, 2011m1 to 2016m12, but with gaps
                delta:  1 month

. xtnbreg TStops FergEff d.UnempL d.OffRateL d.DepScore d.PctNonWhtL  ///
> i.MonthYear if NoCov < 1 & Ped > 0 & weirdPed < 1, fe irr vce(bootstrap, seed(909) ///
> reps(5000) nodots) exposure(population)
note: 683.MonthYear omitted because of collinearity
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered
cannot compute an improvement -- discontinuous region encountered

Conditional FE negative binomial regression     Number of obs     =      1,120
Group variable: PanelID                         Number of groups  =         19

                                                Obs per group:
                                                              min =         15
                                                              avg =       58.9
                                                              max =         71

                                                Wald chi2(74)     =  197665.19
Log likelihood  = -9251.5071                    Prob > chi2       =     0.0000

                                (Replications based on 19 clusters in PanelID)
------------------------------------------------------------------------------
             |   Observed   Bootstrap                         Normal-based
      TStops |        IRR   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     FergEff |   .6192307   .1064706    -2.79   0.005     .4420758    .8673775
             |
      UnempL |
         D1. |   .8374501   .1610524    -0.92   0.356     .5744628    1.220832
             |
    OffRateL |
         D1. |   .6603885   .4228467    -0.65   0.517     .1882674    2.316455
             |
    DepScore |
         D1. |   .9290086    .173211    -0.39   0.693     .6446376    1.338825
             |
  PctNonWhtL |
         D1. |   14.20638    35.9521     1.05   0.294     .0996202    2025.908
             |
   MonthYear |
        614  |   1.146578   .0736061     2.13   0.033      1.01102    1.300312
        615  |   1.006617    .052619     0.13   0.900     .9085933    1.115217
        616  |   1.049894   .0668536     0.76   0.444     .9267099    1.189452
        617  |   1.054525   .0746223     0.75   0.453     .9179574     1.21141
        618  |   1.034053   .0915147     0.38   0.705     .8693815    1.229914
        619  |   1.055636   .0931865     0.61   0.540     .8879207     1.25503
        620  |   .9736106   .0848474    -0.31   0.759     .8207399    1.154955
        621  |   .9153176    .075451    -1.07   0.283     .7787642    1.075815
        622  |   .8882342   .0610208    -1.73   0.084     .7763379    1.016259
        623  |   .8571444   .0625488    -2.11   0.035     .7429146    .9889382
        624  |   .9934036   .1157764    -0.06   0.955     .7905371    1.248329
        625  |   .9549356   .0857258    -0.51   0.607     .8008674    1.138643
        626  |   .9743966   .1113441    -0.23   0.820     .7788774    1.218996
        627  |   .8627593   .0859946    -1.48   0.139     .7096547    1.048895
        628  |   .9477921   .1022488    -0.50   0.619     .7671576    1.170959
        629  |    .883546   .0707767    -1.55   0.122     .7551678    1.033748
        630  |   .8998572   .0986569    -0.96   0.336     .7258571    1.115568
        631  |   .9064308   .1079472    -0.82   0.409      .717736    1.144734
        632  |   .8289902   .0951084    -1.63   0.102     .6620529    1.038021
        633  |   .8599368   .0917442    -1.41   0.157     .6976767    1.059934
        634  |    .814508   .1044704    -1.60   0.110     .6334592    1.047302
        635  |   .7690912     .09871    -2.05   0.041     .5980386    .9890686
        636  |   .9144323   .1129822    -0.72   0.469     .7177642    1.164988
        637  |   .7717637   .0767436    -2.61   0.009     .6350991    .9378367
        638  |   .9603809   .1150642    -0.34   0.736     .7593819    1.214582
        639  |   .8215481   .1079488    -1.50   0.135     .6350206    1.062865
        640  |   .8940645   .1084763    -0.92   0.356     .7048442    1.134082
        641  |   .7996118   .0856263    -2.09   0.037     .6482288    .9863476
        642  |    .799416   .0979943    -1.83   0.068     .6286813    1.016518
        643  |   .8637987   .1066539    -1.19   0.236     .6781317      1.1003
        644  |    .806277   .1079336    -1.61   0.108     .6202072     1.04817
        645  |   .8503716   .1120387    -1.23   0.219     .6568418    1.100923
        646  |   .8065808    .107166    -1.62   0.106     .6216606    1.046508
        647  |   .7392931   .1048281    -2.13   0.033     .5599129    .9761415
        648  |     .84622   .1314907    -1.07   0.283     .6240487    1.147488
        649  |   .7927684   .1111076    -1.66   0.098     .6023504    1.043382
        650  |   .8199199   .1010031    -1.61   0.107     .6440431    1.043826
        651  |   .8024521   .0992945    -1.78   0.075     .6296401    1.022694
        652  |   .8520217   .0925027    -1.48   0.140      .688711    1.054058
        653  |   .7713287   .0788471    -2.54   0.011     .6312881    .9424349
        654  |   .8497398   .0979542    -1.41   0.158     .6778963    1.065145
        655  |   1.339888   .2553733     1.54   0.125     .9222217    1.946711
        656  |   1.270416   .2292642     1.33   0.185     .8919385    1.809494
        657  |   1.239542   .2283402     1.17   0.244     .8638901    1.778541
        658  |   1.095867   .1822236     0.55   0.582     .7910757    1.518091
        659  |   .9734785   .1568437    -0.17   0.868     .7098778    1.334963
        660  |   1.141975    .187839     0.81   0.420     .8272667    1.576403
        661  |   1.083731     .18727     0.47   0.642     .7723831    1.520583
        662  |    1.14873   .1808862     0.88   0.379     .8436892     1.56406
        663  |   1.112143   .1790153     0.66   0.509     .8112371    1.524663
        664  |   1.176683   .1813644     1.06   0.291     .8698858    1.591684
        665  |   1.132981   .1716655     0.82   0.410     .8418827    1.524734
        666  |    1.09567   .1644294     0.61   0.543     .8164662    1.470352
        667  |   1.159367   .1926464     0.89   0.374     .8371064    1.605687
        668  |   1.135509   .1889989     0.76   0.445     .8194324    1.573505
        669  |   1.183655   .1886091     1.06   0.290     .8661455    1.617557
        670  |   1.070044   .1645419     0.44   0.660     .7916104    1.446412
        671  |   .9582003   .1580647    -0.26   0.796     .6934931    1.323947
        672  |   1.194954    .153511     1.39   0.166     .9289683    1.537099
        673  |   1.177753   .0962051     2.00   0.045     1.003514    1.382244
        674  |   1.237498   .0977037     2.70   0.007     1.060083    1.444605
        675  |   1.093451   .0745498     1.31   0.190     .9566779    1.249778
        676  |   1.165388   .0836099     2.13   0.033     1.012515    1.341341
        677  |     1.1584   .0846831     2.01   0.044     1.003766    1.336855
        678  |   1.088442   .0802676     1.15   0.250     .9419614    1.257701
        679  |   1.202126     .10117     2.19   0.029     1.019327    1.417707
        680  |   1.158314   .0876084     1.94   0.052     .9987259    1.343404
        681  |   1.085355   .0653658     1.36   0.174     .9645129    1.221337
        682  |   .9707464   .0401625    -0.72   0.473     .8951364    1.052743
        683  |          1  (omitted)
             |
       _cons |   .0000398   .0000145   -27.89   0.000     .0000195    .0000812
ln(popula~n) |          1  (exposure)
------------------------------------------------------------------------------
Note: _cons estimates baseline incidence rate (conditional on zero random effects).
Note: One or more parameters could not be estimated in 14 bootstrap replicates;
      standard-error estimates include only complete replications.

. estat ic

Akaike's information criterion and Bayesian information criterion

-----------------------------------------------------------------------------
       Model |        Obs  ll(null)  ll(model)      df         AIC        BIC
-------------+---------------------------------------------------------------
           . |      1,120         .  -9251.507      75    18653.01    19029.6
-----------------------------------------------------------------------------
               Note: N=Obs used in calculating BIC; see [R] BIC note.

. 
. log close
      name:  <unnamed>
       log:  /Users/006489466/Dropbox/Depolicing/SubmissionFiles/FergEff/PolicingOX/RnR Round 2/New Analysis Pt
>  2/FergEffTestsStops.log
  log type:  text
 closed on:   6 May 2022, 07:53:49
---------------------------------------------------------------------------------------------------------------
